A Systematic Review of Predictive Analytics Applications in Early Disease Detection and Diagnosis
Downloads
The integration of predictive analytics and artificial intelligence (AI) in healthcare has revolutionized early disease detection and diagnosis, significantly improving patient outcomes and reducing healthcare costs. This systematic review examines the applications of predictive analytics in early-stage disease identification, focusing on AI-driven methodologies, machine learning (ML) algorithms, and big data analytics. By leveraging real-time patient data, electronic health records (EHRs), and genomic information, predictive models enhance diagnostic accuracy, facilitate timely interventions, and optimize healthcare resource allocation. The study explores key predictive modeling techniques, including deep learning, natural language processing (NLP), and ensemble learning, which are applied in early detection of diseases such as cancer, cardiovascular disorders, diabetes, and neurodegenerative conditions. The review assesses the effectiveness of supervised and unsupervised learning models in identifying disease markers, analyzing medical imaging, and predicting disease progression. Additionally, AI-powered wearable devices and remote monitoring systems are highlighted for their role in real-time health tracking and early anomaly detection. A critical aspect of this review is evaluating the challenges associated with predictive analytics in healthcare, including data privacy concerns, bias in AI algorithms, integration issues with existing medical systems, and regulatory constraints. The study also discusses emerging trends, such as federated learning and explainable AI, which aim to enhance model transparency, security, and ethical considerations in clinical decision-making. Findings indicate that AI-driven predictive analytics significantly improve disease prognosis, enabling personalized treatment plans and reducing hospital readmissions. However, widespread adoption requires robust validation, interdisciplinary collaboration, and policy advancements to ensure reliability and fairness in AI-based healthcare solutions. This review provides a comprehensive understanding of predictive analytics applications in disease detection and offers insights into future research directions for enhancing AI-driven healthcare innovations.
Adeghe, E., Okolo, C., & Ojeyinka, O. (2024). A review of the use of machine learning in predictive analytics for patient health outcomes in pharmacy practice. Open Access Research Journal of Life Sciences, 7(1), 052-058.
https://doi.org/10.53022/oarjls.2024.7.1.0026
Adenusi, A., Obi, E., Asifat, O., Magacha, H., Ayinde, A., & Changela, M. (2024). Social determinants of therapeutic endoscopy and procedure time in patients with acute upper gastrointestinal bleeding. The American Journal of Gastroenterology, 119(10S), S581.
https://doi.org/10.14309/01.ajg.0001032740.72909.5b
Adepoju, P. A., Akinade, A. O., Ige, A. B., Afolabi, A. I. (2023). A systematic review of cybersecurity issues in healthcare IT: Threats and solutions. Iconic Research and Engineering Journals, 7(10).
Aderinwale, O., Zheng, S., Mensah, E. A., Boateng, I., Koroma, F. B., Nwajiugo, R. C., ... & Itopa, M. O. (2024). Sociodemographic and behavioral determinants of cervical cancer screening among adult women in the United States.
Adikwu, F. E., Ozobu, C. O., Odujobi, O., Onyeke, F. O., & Nwulu, E. O. (2025). A Comprehensive Review of Health Risk Assessments (HRAs) and Their Impact on Occupational Health Programs in Large-Scale Manufacturing Plants.
Ahmed, A., Brychcy, A., Abouzid, M., Witt, M., & Kaczmarek, E. (2023). Perception of pathologists in poland of artificial intelligence and machine learning in medical diagnosis—a cross-sectional study. Journal of Personalized Medicine, 13(6), 962. https://doi.org/10.3390/jpm13060962
Akerele, J.I., Uzoka, A., Ojukwu, P.U. and Olamijuwon, O.J. (2024). Improving healthcare application scalability through microservices architecture in the cloud. International Journal of Scientific Research Updates. 2024, 08(02), 100–109. https://doi.org/10.53430/ijsru.2024.8.2.0064
Akinmoju, O. D., Olatunji, G., Kokori, E., Ogieuhi, I. J., Babalola, A. E., Obi, E. S., ... & Aderinto, N. (2024). Comparative Efficacy of Continuous Positive Airway Pressure and Antihypertensive Medications in Obstructive Sleep Apnea-Related Hypertension: A Narrative Review. High Blood Pressure & Cardiovascular Prevention, 1-11.
Al Zoubi, M. A. M., Amafah, J., Temedie-Asogwa, T., & Atta, J. A. (2022). International Journal of Multidisciplinary Comprehensive Research.
Alowais, S., Alghamdi, S., Alsuhebany, N., Alqahtani, T., Alshaya, A., Almohareb, S., … & Albekairy, A. (2023). Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education, 23(1). https://doi.org/10.1186/s12909-023-04698-z
Amafah, J., Temedie-Asogwa, T., Atta, J. A., & Al Zoubi, M. A. M. (2023). The Impacts of Treatment Summaries on Patient-Centered Communication and Quality of Care for Cancer Survivors.
Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20(1).
https://doi.org/10.1186/s12911-020-01332-6
Amedior, N. (2023). Ethical implications of artificial intelligence in the healthcare sector. Advances in Multidisciplinary & Scientific Research Journal Publication, 36, 1-12.
https://doi.org/10.22624/aims-/accrabespoke2023p1
Ansari, Z., Tripathi, M., & Ahmed, R. (2024). Understanding the landscape: a review of explainable ai in healthcare decision-making.. https://doi.org/10.21203/rs.3.rs-4908320/v1
Apeh, C. E., Odionu, C. S., Bristol-Alagbariya, B., Okon, R., & Austin-Gabriel, B. (2024). Reviewing healthcare supply chain management: Strategies for enhancing efficiency and resilience. International Journal of Research and Scientific Innovation (IJRSI), 5(1), 1209-1216.
DOI:https://doi.org/10.54660/.IJMRGE.2024.5.1.1209-1216
Arowoogun, J., Babawarun, O., Chidi, R., Adeniyi, A., & Okolo, C. (2024). A comprehensive review of data analytics in healthcare management: leveraging big data for decision-making. World Journal of Advanced Research and Reviews, 21(2), 1810-1821. https://doi.org/10.30574/wjarr.2024.21.2.0590
Atandero, M.O., Fasipe, O.J., Famakin, S.M. and Ogunboye, I., (2024). A cross-sectional survey of comorbidity profile among adult Human Immunodeficiency Virus-infected patients attending a Nigeria medical university teaching hospital campus located in Akure, Ondo State. Archives of Medicine and Health Sciences, [online] Available at: https://doi.org/10.4103/amhs.amhs_94_24.
Atta, J. A., Al Zoubi, M. A. M., Temedie-Asogwa, T., & Amafah, J. (2021): Comparing the Cost-Effectiveness of Pharmaceutical vs. Non-Pharmaceutical Interventions for Diabetes Management.
Ayo-Farai, O., Ogundairo, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2023). Telemedicine in Health Care: A Review of Progress and Challenges in Africa. Matrix Science Pharma, 7(4), 124-132.
Ayo-Farai, O., Ogundairo, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2024). Digital Health Technologies in Chronic Disease Management: A Global Perspective. International Journal of Research and Scientific Innovation, 10(12), 533-551.
Babarinde, A. O., Ayo-Farai, O., Maduka, C. P., Okongwu, C. C., & Sodamade, O. (2023). Data analytics in public health, A USA perspective: A review. World Journal of Advanced Research and Reviews, 20(3), 211-224.
Babarinde, A. O., Ayo-Farai, O., Maduka, C. P., Okongwu, C. C., Ogundairo, O., & Sodamade, O. (2023). Review of AI applications in Healthcare: Comparative insights from the USA and Africa. International Medical Science Research Journal, 3(3), 92-107.
Babarinde, A. O., Balogun, M. R., & Odugbemi, T. O. (2018). Knowledge, attitude and use of mobile phones to acquire health-related information among students of Yaba College of Technology, Lagos.
Badawy, M., Ramadan, N., & Hefny, H. (2023). Healthcare predictive analytics using machine learning and deep learning techniques: a survey. Journal of Electrical Systems and Information Technology, 10(1). https://doi.org/10.1186/s43067-023-00108-y
Balogun, O. D., Ayo-Farai, O., Ogundairo, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2023). Innovations in drug delivery systems: A review of the pharmacist's role in enhancing efficacy and patient compliance.
Balogun, O. D., Ayo-Farai, O., Ogundairo, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2023). Integrating AI into health informatics for enhanced public health in Africa: a comprehensive review. International Medical Science Research Journal, 3(3), 127-144.
Balogun, O. D., Ayo-Farai, O., Ogundairo, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2024). The Role of pharmacists in personalised medicine: a review of integrating pharmacogenomics into clinical practice. International Medical Science Research Journal, 4(1), 19-36.
Batko, K. and Ślęzak, A. (2022). The use of big data analytics in healthcare. Journal of Big Data, 9(1). https://doi.org/10.1186/s40537-021-00553-4
Bhatt, A. (2024). Development of ai-driven healthcare systems in rural india. AJCET, 5(1), 21-30. https://doi.org/10.47604/ajcet.2808
Bidemi, A. I., Oyindamola, F. O., Odum, I., Stanley, O. E., Atta, J. A., Olatomide, A. M., ... & Helen, O. O. (2021). Challenges Facing Menstruating Adolescents: A Reproductive Health Approach. Journal of Adolescent Health, 68(5), 1-10.
Borhade, R. (2024). Ai-enhanced predictive analytics for proactive healthcare management: leveraging machine learning to improve patient care and operational efficiency. pmj, 35(1s), 46-57. https://doi.org/10.52783/pmj.v35.i1s.2096
Chatterjee, P., Cymberknop, L., & Armentano, R. (2020). Nonlinear systems in healthcare towards intelligent disease prediction.. https://doi.org/10.5772/intechopen.88163
Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024). Health data analytics for precision medicine: A review of current practices and future directions. International Medical Science Research Journal, 4(11), 973-984.
https://www.fepbl.com/index.php/imsrj/article/view/1732
Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024). Predictive analytics in emergency healthcare systems: A conceptual framework for reducing response times and improving patient care. World Journal of Advanced Pharmaceutical and Medical Research, 07(2), 119–127. https://zealjournals.com/wjapmr/content/predictive-analytics-emergency-healthcare-systems-conceptual-framework-reducing-response
Coorey, G., Figtree, G., Fletcher, D., Snelson, V., Vernon, S., Winlaw, D., … & Redfern, J. (2022). The health digital twin to tackle cardiovascular disease—a review of an emerging interdisciplinary field. NPJ Digital Medicine, 5(1). https://doi.org/10.1038/s41746-022-00640-7
Cozzoli et al. "How Can Big Data Analytics Be Used for Healthcare Organization Management? Literary Framework and Future Research from a Systematic Review" BMC Health Services Research (2022) doi:10.1186/s12913-022-08167-z.
Cozzoli, N., Salvatore, F., Faccilongo, N., & Milone, M. (2022). How can big data analytics be used for healthcare organization management? literary framework and future research from a systematic review. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-08167-z
Dirlikov, E. (2021). Rapid scale-up of an antiretroviral therapy program before and during the COVID-19 pandemic—nine states, Nigeria, March 31, 2019–September 30, 2020. MMWR. Morbidity and Mortality Weekly Report, 70.
Dirlikov, E., Jahun, I., Odafe, S. F., Obinna, O., Onyenuobi, C., Ifunanya, M., ... & Swaminathan, M. (2021). Section navigation rapid scale-up of an antiretroviral therapy program before and during the COVID-19 pandemic-nine states, Nigeria, March 31, 2019-September 30, 2020.
Edoh, N. L., Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024). Improving healthcare decision-making with predictive analytics: A conceptual approach to patient risk assessment and care optimization. International Journal of Scholarly Research in Medicine and Dentistry, 03(2), 001–010.
https://srrjournals.com/ijsrmd/sites/default/files/IJSRMD-2024-0034.pdf
Edoh, N. L., Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024). The role of data analytics in reducing healthcare disparities: A review of predictive models for health equity. International Journal of Management & Entrepreneurship Research, 6(11), 3819-3829. https://www.fepbl.com/index.php/ijmer/article/view/1721
Edoh, N., Chigboh, V., Zouo, S., & Olamijuwon, J. (2024). The role of data analytics in reducing healthcare disparities: a review of predictive models for health equity. International Journal of Management & Entrepreneurship Research, 6(11), 3819-3829. https://doi.org/10.51594/ijmer.v6i11.1721
Efobi, C. C., Nri-ezedi, C. A., Madu, C. S., Obi, E., Ikediashi, C. C., & Ejiofor, O. (2023). A Retrospective Study on Gender-Related Differences in Clinical Events of Sickle Cell Disease: A Single Centre Experience. Tropical Journal of Medical Research, 22(1), 137-144.
Efobi, C. C., Obi, E. S., Faniyi, O., Offiah, C. E., Okam, O. V., Ndubuisi, O. J., ... & Umeh, O. E. (2025). The impact of ABO blood group on the prevalence of transfusion-transmitted infections among blood donors in a tertiary-care hospital. American Journal of Clinical Pathology, aqae162.
Egevad, L., Swanberg, D., Delahunt, B., Ström, P., Kartasalo, K., Olsson, H., … & Eklund, M. (2020). Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading. Virchows Archiv, 477(6), 777-786. https://doi.org/10.1007/s00428-020-02858-w
Ejjami, R. (2024). AI-driven healthcare in France. International Journal for Multidisciplinary Research (IJFMR240322936), 6(3).
Elufioye, O. A., Ndubuisi, N. L., Daraojimba, R. E., Awonuga, K. F., Ayanponle, L. O., & Asuzu, O. F. (2024). Reviewing employee well-being and mental health initiatives in contemporary HR Practices. International Journal of Science and Research Archive, 11(1), 828-840.
Elujide, I., Fashoto, S. G., Fashoto, B., Mbunge, E., Folorunso, S. O., & Olamijuwon, J. O. (2021). Informatics in Medicine Unlocked.
Elujide, I., Fashoto, S. G., Fashoto, B., Mbunge, E., Folorunso, S. O., & Olamijuwon, J. O. (2021). Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases. Informatics in Medicine Unlocked, 23,
Ennab, M. and Mcheick, H. (2022). Designing an interpretability-based model to explain the artificial intelligence algorithms in healthcare. Diagnostics, 12(7), 1557. https://doi.org/10.3390/diagnostics12071557
Fagbule, O. F., Amafah, J. O., Sarumi, A. T., Ibitoye, O. O., Jakpor, P. E., & Oluwafemi, A. M. (2023). Sugar-Sweetened Beverage Tax: A Crucial Component of a Multisectoral Approach to Combating Non-Communicable Diseases in Nigeria. Nigerian Journal of Medicine, 32(5), 461-466.
Fasipe, O.J. & Ogunboye, I., (2024). Elucidating and unravelling the novel antidepressant mechanism of action for atypical antipsychotics: repurposing the atypical antipsychotics for more comprehensive therapeutic usage. RPS Pharmacy and Pharmacology Reports, 3(3), p. rqae017. Available at: https://doi.org/10.1093/rpsppr/rqae017
Gates, J., Yulianti, Y., & Pangilinan, G. (2024). Big data analytics for predictive insights in healthcare. International Transactions on Artificial Intelligence (Italic), 3(1), 54-63.
https://doi.org/10.33050/italic.v3i1.622
Ghawate, P. (2024). Handling unstructured image using generative ai and dev-ops. International Journal for Research in Applied Science and Engineering Technology, 12(4), 3340-3350. https://doi.org/10.22214/ijraset.2024.60599
Gupta, B., Rawat, A., Jain, A., Arora, A., & Dhami, N. (2017). Analysis of various decision tree algorithms for classification in data mining. International Journal of Computer Applications, 163(8), 15-19.
https://doi.org/10.5120/ijca2017913660
Halabhavi, B. (2024). Ai-driven predictive analytics in healthcare: improving patient outcomes and resource allocation. AJBR, 9288-9297. https://doi.org/10.53555/ajbr.v27i4s.5427
Han, Q., Dong, B., Yuan, J., Yin, F., Wang, Z., Wang, H., … & Ning, B. (2021). Pre-consultation system based on the artificial intelligence has a better diagnostic performance than the physicians in the outpatient department of pediatrics. Frontiers in Medicine, 8.
https://doi.org/10.3389/fmed.2021.695185
Hanada, E. (2020). Potential problems and uses for artificial intelligence in clinical medicine. International Journal of Computer & Software Engineering, 5(1). https://doi.org/10.15344/2456-4451/2020/154
Handayani, I., Apriani, D., Mulyati, M., Zahra, A., & Yusuf, N. (2023). Enhancing security and privacy of patient data in healthcare: a smartpls analysis of blockchain technology implementation. Iaic Transactions on Sustainable Digital Innovation (Itsdi), 5(1), 8-17.
https://doi.org/10.34306/itsdi.v5i1.603
Harada, Y., Katsukura, S., Kawamura, R., & Shimizu, T. (2021). Efficacy of artificial-intelligence-driven differential-diagnosis list on the diagnostic accuracy of physicians: an open-label randomized controlled study. International Journal of Environmental Research and Public Health, 18(4), 2086.
https://doi.org/10.3390/ijerph18042086
Hirasawa, T., Aoyama, K., Tanimoto, T., Ishihara, S., Shichijo, S., Ozawa, T., … & Tada, T. (2018). Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images. Gastric Cancer, 21(4), 653-660. https://doi.org/10.1007/s10120-018-0793-2
Ibeh et al. "Data Analytics in Healthcare: A Review of Patient-Centric Approaches and Healthcare Delivery" World Journal of Advanced Research and Reviews (2024)
doi:10.30574/wjarr.2024.21.2.0246.
Ibeh, A.I., Oso, O.B., Alli, O.I., & Babarinde, A.O. (2025) 'Scaling healthcare startups in emerging markets: A platform strategy for growth and impact', International Journal of Advanced Multidisciplinary Research and Studies, 5(1), pp. 838-854. Available at: http://www.multiresearchjournal.com/
Ibeh, C., Elufioye, O., Olorunsogo, T., Asuzu, O., Nduubuisi, N., & Daraojimba, A. (2024). Data analytics in healthcare: a review of patient-centric approaches and healthcare delivery. World Journal of Advanced Research and Reviews, 21(2), 1750-1760. https://doi.org/10.30574/wjarr.2024.21.2.0246
Jahun, I., Dirlikov, E., Odafe, S., Yakubu, A., Boyd, A. T., Bachanas, P., ... & CDC Nigeria ART Surge Team. (2021). Ensuring optimal community HIV testing services in Nigeria using an enhanced community case-finding package (ECCP), October 2019–March 2020: acceleration to HIV epidemic control. HIV/AIDS-Research and Palliative Care, 839-850.
Jahun, I., Said, I., El-Imam, I., Ehoche, A., Dalhatu, I., Yakubu, A., ... & Swaminathan, M. (2021). Optimizing community linkage to care and antiretroviral therapy Initiation: Lessons from the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) and their adaptation in Nigeria ART Surge. PLoS One, 16(9), e0257476.
Jamarani, A., Haddadi, S., Sarvizadeh, R., Haghi Kashani, M., Akbari, M., & Moradi, S. (2024). Big data and predictive analytics: A systematic review of applications. Artificial Intelligence Review, 57(7), 176.
Jhajharia, S., Pal, S. K., Verma, S., & Kumar, M. (2015). Predictive analytics for better health and disease reduction. In 1st IIMA International Conference on Advances in Healthcare Management Services. Indian Institute of Management, Ahmedabad.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 2(4), 230-243. https://doi.org/10.1136/svn-2017-000101
Kedi, W. E., Ejimuda, C., & Ajegbile, M. D. (2024). Cloud computing in healthcare: A comprehensive review of data storage and analysis solutions. World Journal of Advanced Engineering Technology and Sciences, 12(2), 290-298.
Khan, F., Masum, A., Adam, J., Karim, M., & Afrin, S. (2024). Ai in healthcare supply chain management: enhancing efficiency and reducing costs with predictive analytics. Journal of Computer Science and Technology Studies, 6(5), 85-93. https://doi.org/10.32996/jcsts.2024.6.5.8
Koraishy and Mallipattu "Dialysis Resource Allocation in Critical Care: The Impact of the COVID-19 Pandemic and the Promise of Big Data Analytics" Frontiers in Nephrology (2023) doi:10.3389/fneph.2023.1266967.
Koroma, F., Aderinwale, O. A., Obi, E. S., Campbell, C., Itopa, M. O., Nwajiugo, R. C., ... & Ayo-Bali, O. E. (2024). Socio-demographic and behavioral predictors of Depression among Veterans in the USA.
Kosaraju "Predictive Analytics in Healthcare: Leveraging AI to Anticipate Disease Outbreaks and Enhance Patient Outcomes" Galore International Journal of Health Sciences and Research (2024) doi:10.52403/gijhsr.20230312.
Kumar, V., & Garg, M. L. (2018). Predictive analytics: a review of trends and techniques. International Journal of Computer Applications, 182(1), 31-37.
Kumbhar, E. (2024). Explainable ai-powered iot systems for predictive and preventive healthcare - a framework for personalized health management and wellness optimization. jes, 19(3), 23-31.
https://doi.org/10.52783/jes.648
Kuwahara, T., Hara, K., Mizuno, N., Haba, S., Okuno, N., Koda, H., … & Fumihara, D. (2020). Current status of artificial intelligence analysis for endoscopic ultrasonography. Digestive Endoscopy, 33(2), 298-305. https://doi.org/10.1111/den.13880
Lee, D. and Yoon, S. (2021). Application of artificial intelligence-based technologies in the healthcare industry: opportunities and challenges. International Journal of Environmental Research and Public Health, 18(1), 271. https://doi.org/10.3390/ijerph18010271
Lee, K. and Kim, E. (2022). Explainable artificial intelligence in the early diagnosis of gastrointestinal disease. Diagnostics, 12(11), 2740. https://doi.org/10.3390/diagnostics12112740
Leung, C., Fung, D., Mushtaq, S., Leduchowski, O., Bouchard, R., Jin, H., … & Zhang, C. (2020). Data science for healthcare predictive analytics., 1-10. https://doi.org/10.1145/3410566.3410598
Madi, I., Redjdal, A., Bouaud, J., & Séroussi, B. (2024). Exploring explainable ai techniques for text classification in healthcare: a scoping review.. https://doi.org/10.3233/shti240544
Makubhai, S., Pathak, G., & Chandre, P. (2023). Prevention in healthcare: an explainable ai approach. International Journal on Recent and Innovation Trends in Computing and Communication, 11(5), 92-100.
https://doi.org/10.17762/ijritcc.v11i5.6582
Mbakop, R. N. S., Forlemu, A. N., Ugwu, C., Soladoye, E., Olaosebikan, K., Obi, E. S., & Amakye, D. (2024). Racial Differences in Non-variceal Upper Gastrointestinal (GI) Bleeding: A Nationwide Study. Cureus, 16(6).
Mienye, I., Obaido, G., Jere, N., Mienye, E., Aruleba, K., Emmanuel, I., … & Ogbuokiri, B. (2024). A survey of explainable artificial intelligence in healthcare: concepts, applications, and challenges..
https://doi.org/10.20944/preprints202408.1702.v1
Mucci, A., Green, W., & Hill, L. (2024). Incorporation of artificial intelligence in healthcare professions and patient education for fostering effective patient care. New Directions for Adult and Continuing Education, 2024(181), 51-62.
https://doi.org/10.1002/ace.20521
Neupane, H., Ahuja, M., Ghimire, A., Itopa, M. O., Osei, P. A., & Obi, E. S. (2024). Excessive alcohol consumption and increased risk of heart attack.
Nia, N., Kaplanoğlu, E., & Nasab, A. (2023). Evaluation of artificial intelligence techniques in disease diagnosis and prediction. Discover Artificial Intelligence, 3(1). https://doi.org/10.1007/s44163-023-00049-5
Nor, N., Mohamed, A., & Mutalib, S. (2020). Prevalence of hypertension: predictive analytics review. Iaes International Journal of Artificial Intelligence (Ij-Ai), 9(4), 576.
https://doi.org/10.11591/ijai.v9.i4.pp576-583
Nwokedi, C. N., Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., & Iguma, D. R. (2025). Virtual Reality (VR) and Augmented Reality (AR) in Medicine: A review of clinical applications. International Journal of Scientific Research in Science, Engineering and Technology, 11(6), 438-449.
https://doi.org/10.32628/IJSERSET242435
Nwokedi, C. N., Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., Iguma, D. R., & Forkuo, A. Y. (2024). Robotics in healthcare: A systematic review of robotic-assisted surgery and rehabilitation. International Journal of Scientific Research in Science and Technology, 11(6), 1061-1074.
https://doi.org/10.32628/IJSRST25121246
Nwokedi, C. N., Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., & Iguma, D. R. (2024). Virtual Reality (VR) and Augmented Reality (AR) in Medicine: A review of clinical applications. International Journal of Scientific Research in Science, Engineering and Technology, 11(6), 438-449.
https://doi.org/10.32628/IJSERSET242435
Nwokedi, C. N., Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., & Iguma, D. R. (2024). Robotics in healthcare: A systematic review of robotic-assisted surgery and rehabilitation. International Journal of Scientific Research in Science and Technology, 11(6), 1061-1074. https://doi.org/10.32628/IJSRST25121246
Nwokedi, C. N., Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., & Iguma, D. R. (2025). Telemedicine implementation in rural areas: Technical solutions and policy recommendations. International Medical Science Research Journal, 10(1), 1-12.
https://doi.org/10.51594/imsrj.v5i1.
Obi, E. S., Devdat, L. N. U., Ehimwenma, N. O., Tobalesi, O., Iklaki, W., & Arslan, F. (2023). Immune Thrombocytopenia: A Rare Adverse Event of Vancomycin Therapy. Cureus, 15(5).
Obi, E. S., Devdat, L. N. U., Ehimwenma, N. O., Tobalesi, O., Iklaki, W., Arslan, F., ... & Iklaki, W. U. (2023). Immune Thrombocytopenia: a rare adverse event of Vancomycin
Therapy. Cureus, 15(5).
Obi, E., Aderinwale, O. A., Ugwuoke, U., Okam, O., Magacha, H., & Itopa, M. O. (2024). Evaluating and Improving Patient and Family Satisfaction with Hemato-Oncological Services at an Outpatient Clinic in East Tennessee: A Service Excellence Initiative.
Obijuru, A., Arowoogun, J., Onwumere, C., Odilibe, I., Anyanwu, E., & Daraojimba, A. (2024). Big data analytics in healthcare: a review of recent advances and potential for personalized medicine. International Medical Science Research Journal, 4(2), 170-182. https://doi.org/10.51594/imsrj.v4i2.810
Odionu, C. S., & Ibeh, C. V. (2023). Big data analytics in healthcare: A comparative review of USA and global use cases. Journal Name, 4(6), 1109-1117.
DOI:https://doi.org/10.54660/.IJMRGE.2023.4.6.1109-1117
Ogieuhi, I. J., Callender, K., Odukudu, G. D. O., Obi, E. S., Muzofa, K., Babalola, A. E., ... & Odoeke, M. C. (2024). Antisense Oligonucleotides in Dyslipidemia Management: A Review of Clinical Trials. High Blood Pressure & Cardiovascular Prevention, 1-15.
Ogugua, J., Onwumere, C., Arowoogun, J., Anyanwu, E., Odilibe, I., & Akomolafe, O. (2024). Data science in public health: a review of predictive analytics for disease control in the usa and africa. World Journal of Advanced Research and Reviews, 21(1), 2753-2769.
https://doi.org/10.30574/wjarr.2024.21.1.0383
Ogunboye, I., Adebayo, I.P.S., Anioke, S.C., Egwuatu, E.C., Ajala, C.F. and Awuah, S.B. (2023) ‘Enhancing Nigeria’s health surveillance system: A data-driven approach to epidemic preparedness and response’, World Journal of Advanced Research and Reviews, 20(1). Available at:
https://doi.org/10.30574/wjarr.2023.20.1.2078.
Ogunboye, I., Momah, R., Myla, A., Davis, A. and Adebayo, S. (2024) ‘HIV screening uptake and disparities across socio-demographic characteristics among Mississippi adults: Behavioral Risk Factor Surveillance System (BRFSS), 2022’, HPHR, 88. Available at: https://doi.org/10.54111/0001/JJJJ3.
Ogunboye, I., Zhang, Z. & Hollins, A., (2024). The predictive socio-demographic factors for HIV testing among the adult population in Mississippi. HPHR, 88. Available at:
https://doi.org/10.54111/0001/JJJJ1.
Ogundairo, O., Ayo-Farai, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2023). Review on MALDI mass spectrometry and its application in clinical research. International Medical Science Research Journal, 3(3), 108-126.
Ogundairo, O., Ayo-Farai, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. T. (2024). Review on MALDI Imaging for Direct Tissue Imaging and its Application in Pharmaceutical Research. International Journal of Research and Scientific Innovation, 10(12), 130-141.
Ogundairo, O., Ayo-Farai, O., Maduka, C. P., Okongwu, C. C., Babarinde, A. O., & Sodamade, O. (2023). Review On Protein Footprinting As A Tool In Structural Biology. Science Heritage Journal (GWS), 7(2), 83-90.
Ogungbenle, H. N., & Omowole, B. M. (2012). Chemical, functional and amino acid composition of periwinkle (Tympanotonus fuscatus var radula) meat. Int J Pharm Sci Rev Res, 13(2), 128-132.
Oh, S., Kim, J., Choi, S., Lee, H., Hong, J., & Kwon, S. (2019). Physician confidence in artificial intelligence: an online mobile survey. Journal of Medical Internet Research, 21(3), e12422. https://doi.org/10.2196/12422
Ojo, O. and Kiobel, B. (2024). The impact of business analytics on healthcare operations: a statistical perspective. World Journal of Biology Pharmacy and Health Sciences, 19(3), 205-217. https://doi.org/10.30574/wjbphs.2024.19.3.0625
Okolie, C. I., Hamza, O., Eweje, A., Collins, A., & Babatunde, G. O. (2021). Leveraging Digital Transformation and Business Analysis to Improve Healthcare Provider Portal. IRE Journals, 4(10), 253-254. https://doi.org/10.54660/IJMRGE.2021.4.10.253-254:contentReference[oaicite:0]{index=0
Okpujie, V. O., Uwumiro, F. E., Bojerenu, M., Alemenzohu, H., Obi, E. S., Chigbu, N. C., ... & Obidike, A. (2024, March). Increased ventilator utilization, ventilator-associated pneumonia, and mortality in non-COVID patients during the pandemic. In Baylor University Medical Center Proceedings (Vol. 37, No. 2, pp. 230-238). Taylor & Francis.
Olamijuwon and Zouo "The Impact of Health Analytics on Reducing Healthcare Costs in Aging Populations: A Review" International Journal of Management & Entrepreneurship Research (2024) doi:10.51594/ijmer.v6i11.1690.
Olamijuwon, J., & Zouo, S. J. C. (2024). The impact of health analytics on reducing healthcare costs in aging populations: A review. International Journal of Management & Entrepreneurship Research. https://www.fepbl.com/index.php/ijmer/article/view/1690
Olamijuwon, J., Akerele, J. I., Uzoka, A., & Ojukwu, P. U. (2024). Improving response times in emergency services through optimized Linux server environments. International Journal of Engineering Research and Development, 20(11), 1111–1119. International Journal of Engineering Research and Development
Olaniyi et al. "Harnessing Predictive Analytics for Strategic Foresight: A Comprehensive Review of Techniques and Applications in Transforming Raw Data to Actionable Insights" Asian Journal of Economics Business and Accounting (2023) doi:10.9734/ajeba/2023/v23i221164.
Olaniyi, F., Olaniyi, O., Adigwe, C., Abalaka, A., & Shah, N. (2023). Harnessing predictive analytics for strategic foresight: a comprehensive review of techniques and applications in transforming raw data to actionable insights. Asian Journal of Economics Business and Accounting, 23(22), 441-459. https://doi.org/10.9734/ajeba/2023/v23i221164
Olatunji, G., Kokori, E., Ogieuhi, I. J., Abraham, I. C., Olanisa, O., Nzeako, T., ... & Aderinto, N. (2024). Can CSL-112 Revolutionize Atherosclerosis Treatment? A Critical Look at the Evidence. Current Problems in Cardiology, 102680.
Olorunsogo, T., Adenyi, A., Okolo, C., & Babawarun, O. (2024). Ethical considerations in ai-enhanced medical decision support systems: a review. World Journal of Advanced Engineering Technology and Sciences, 11(1), 329-336. https://doi.org/10.30574/wjaets.2024.11.1.0061
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Conceptual frameworks and innovative biostatistical approaches for advancing public health research initiatives. International Journal of Scholarly Research in Medicine and Dentistry, 03(2), 011–021.
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Comprehensive review of advanced data analytics techniques for enhancing clinical research outcomes. International Journal of Scholarly Research in Biology and Pharmacy, 05(1), 008–017. https://srrjournals.com/ijsrbp/content/comprehensive-review-advanced-data-analytics-techniques-enhancing-clinical-research-outcomes
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Comprehensive review of logistic regression techniques in predicting health outcomes and trends. World Journal of Advanced Pharmaceutical and Life Sciences, 07(2), 016–026. https://zealjournals.com/wjapls/sites/default/files/WJAPLS-2024-0039.pdf
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Conceptual review on the importance of data visualization tools for effective research communication.
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Conceptual frameworks and innovative biostatistical approaches for advancing public health research initiatives. International Journal of Scholarly Research in Medicine and Dentistry, 3(2). Scholarly Research and Reviews.
Olowe, K. J., Edoh, N. L., Zouo, S. J. C., & Olamijuwon, J. (2024). Theoretical perspectives on biostatistics and its multifaceted applications in global health studies. International Journal of Applied Research in Social Sciences, 6(11), 2791-2806. https://www.fepbl.com/index.php/ijarss/article/view/1726
Ooge, J., Štiglic, G., & Verbert, K. (2021). Explaining artificial intelligence with visual analytics in healthcare. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, 12(1). https://doi.org/10.1002/widm.1427
Oso, O. B., Alli, O. I., Babarinde, A. O., & Ibeh, A. I. (2025). Navigating cross-border healthcare investments: A risk-opportunity model for emerging markets. Engineering and Technology Journal, 10(2), 3805-3832. DOI
Oso, O. B., Alli, O. I., Babarinde, A. O., & Ibeh, A. I. (2025). Private equity and value creation in healthcare: A strategic model for emerging markets. International Journal of Medical and All Body Health Research, 6(1), 55-73. DOI
Oso, O. B., Alli, O. I., Babarinde, A. O., & Ibeh, A. I. (2025). Blended financing models for healthcare development: Unlocking capital for sustainable infrastructure in frontier markets. International Journal of Management and Organizational Research, 4(1), 63-81. DOI
Oso, O.B., Alli, O.I., Babarinde, A.O. & Ibeh, A.I. (2025) 'Advanced financial modeling in healthcare investments: A framework for optimizing sustainability and impact', Gulf Journal of Advance Business Research, 3(2), pp. 561-589. Available at: https://doi.org/10.51594/gjabr.v3i2.98
Oso, O.B., Alli, O.I., Babarinde, A.O., & Ibeh, A.I. (2025) 'Impact-driven healthcare investments: A conceptual framework for deploying capital and technology in frontier markets', International Journal of Multidisciplinary Research and Growth Evaluation, 6(1), pp. 1702-1720. Available at: https://doi.org/10.54660/IJMRGE.2025.6.1.1702-1720
Oso, O.B., Alli, O.I., Babarinde, A.O., & Ibeh, A.I. (2025) 'Private equity and value creation in healthcare: A strategic model for emerging markets', International Journal of Medical and All Body Health Research, 6(1), pp. 55-73. Available at: https://doi.org/10.54660/IJMBHR.2025.6.1.55-73
Owoade, S.J., Uzoka, A., Akerele, J.I. & Ojukwu, P.U., 2024. Innovative cross-platform health applications to improve accessibility in underserved communities. International Journal of Applied Research in Social Sciences, 6(11), pp. 2727–2743.
Owoade, S.J., Uzoka, A., Akerele, J.I. and Ojukwu, P.U. (2024). Innovative cross-platform health applications to improve accessibility in underserved communities. International Journal of Applied Research in Social Sciences. P-ISSN: 2706-9176, E-ISSN: 2706-9184 Volume 6, Issue 11, P.No. 2727-2743, November 2024.
DOI:10.51594/ijarss.v6i11.1723: http://www.fepbl.com/index.php/ijarss
Ozobu, C. O., Adikwu, F., Odujobi, O., Onyekwe, F. O., & Nwulu, E. O. (2025). Developing an AI-powered occupational health surveillance system for real-time detection and management of workplace health hazards. World Journal of Innovation and Modern Technology, 9(1), 156–185. International Institute of Academic Research and Development.
Ozobu, C. O., Adikwu, F., Odujobi, O., Onyekwe, F. O., & Nwulu, E. O. (2025). A review of health risk assessment and exposure control models for hazardous waste management operations in Africa. International Journal of Advanced Multidisciplinary Research and Studies, 5(2), 570–582.
Pan, Y. and Jiao, F. (2024). Application of artificial intelligence in the diagnosis and treatment of kawasaki disease. World Journal of Clinical Cases, 12(23), 5304-5307. https://doi.org/10.12998/wjcc.v12.i23.5304
Paul, P. O., Abbey, A. B. N., Onukwulu, E. C., Agho, M. O., & Louis, N. (2021). Integrating procurement strategies for infectious disease control: Best practices from global programs. prevention, 7, 9.
Paul, P. O., Abbey, A. B. N., Onukwulu, E. C., Eyo-Udo, N. L., & Agho, M. O. (2024). Sustainable supply chains for disease prevention and treatment: Integrating green logistics. Int J Multidiscip Res Growth Eval, 5(6), 2582-7138.
Paul, P. O., Ogugua, J. O., & Eyo-Udo, N. L. (2024). Procurement in healthcare: Ensuring efficiency and compliance in medical supplies and equipment management.
Peng, X., Long, G., Wang, S., Jiang, J., Clarke, A., Schlegel, C., … & Zhang, C. (2021). Mipo: mutual integration of patient journey and medical ontology for healthcare representation learning.. https://doi.org/10.48550/arxiv.2107.09288
Petersson, L., Larsson, I., Nygren, J., Nilsén, P., Neher, M., Reed, J., … & Svedberg, P. (2022). Challenges to implementing artificial intelligence in healthcare: a qualitative interview study with healthcare leaders in sweden. BMC Health Services Research, 22(1). https://doi.org/10.1186/s12913-022-08215-8
Pournik, O., Mukherjee, T., Ghalichi, L., & Arvanitis, T. (2023). How interoperability challenges are addressed in healthcare iot projects.. https://doi.org/10.3233/shti230754
Ramya, R., & Ramamoorthy, S. (2024). Hybrid fog-edge-IoT architecture for real-time data monitoring. International Journal of Intelligent Engineering and Systems, 17(1), 228–239.
Reddy, S., Lebrun, A., Chee, A., & Kalogeropoulos, D. (2024). Discussing the role of explainable ai and evaluation frameworks for safe and effective integration of large language models in healthcare. Telehealth and Medicine Today, 9(2). https://doi.org/10.30953/thmt.v9.485
Rohith, J. and Priyadarsini, P. (2023). Classification and prediction of chronic kidney disease using novel decision tree algorithm by comparing random forest for obtaining better accuracy. CM, (25), 1800-1807. https://doi.org/10.18137/cardiometry.2022.25.18001807
Sarwar, S., Dent, A., Faust, K., Richer, M., Djuric, U., Ommeren, R., … & Diamandis, P. (2019). Physician perspectives on integration of artificial intelligence into diagnostic pathology. NPJ Digital Medicine, 2(1). https://doi.org/10.1038/s41746-019-0106-0
Scheetz, J., Rothschild, P., McGuinness, M., Hadoux, X., Soyer, H., Janda, M., … & Wijngaarden, P. (2021). A survey of clinicians on the use of artificial intelligence in ophthalmology, dermatology, radiology and radiation oncology. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-84698-5
Schuver, T., Sathiyaseelan, T., Ukoha, N., Annor, E., Obi, E., Karki, A., ... & Aderinwale, O. (2024). Excessive Alcohol Consumption and Heart Attack Risk. Circulation, 150(Suppl_1), A4146639-A4146639.
Shang, Z., Chauhan, V., Devi, K., & Patil, S. (2024). Artificial intelligence, the digital surgeon: unravelling its emerging footprint in healthcare – the narrative review. Journal of Multidisciplinary Healthcare, Volume 17, 4011-4022. https://doi.org/10.2147/jmdh.s482757
Sharma, R. (2020). Artificial intelligence in healthcare: a review. Turkish Journal of Computer and Mathematics Education (Turcomat), 11(1), 1663-1667. https://doi.org/10.61841/turcomat.v11i1.14628
Shittu, R. A., Ehidiamen, A. J., Ojo, O. O., Zouo, S. J. C., Olamijuwon, J., Omowole, B. M., & Olufemi-Phillips, A. Q. (2024). The role of business intelligence tools in improving healthcare patient outcomes and operations. World Journal of Advanced Research and Reviews, 24(2), 1039–1060. https://wjarr.com/sites/default/files/WJARR-2024-3414.pdf
Shittu, R. A., Ehidiamen, A. J., Ojo, O. O., Zouo, S. J. C., Olamijuwon, J., & Omowole, B. M. (2024). The role of business intelligence tools in improving healthcare patient outcomes and operations. World Journal of Advanced Research and Reviews. Retrieved from https://www.semanticscholar.org/paper/9fc78dbc9bbe5a707e555973ae986f7d8755e5f3
Shittu, R.A., Ehidiamen, A.J., Ojo, O.O., Zouo, S.J.C., Olamijuwon, J., Omowole, B.M., and Olufemi-Phillips, A.Q., 2024. The role of business intelligence tools in improving healthcare patient outcomes and operations. World Journal of Advanced Research and Reviews, 24(2), pp.1039–1060. Available at: https://doi.org/10.30574/wjarr.2024.24.2.3414.
Singh, A., Wan, M., Harrison, L., Breggia, A., Christman, R., Winslow, R., … & Amal, S. (2022). Visualizing decisions and analytics of artificial intelligence based cancer diagnosis and grading of specimen digitized biopsy: case study for prostate cancer.. https://doi.org/10.1101/2022.12.21.22283754
Solfa, F. and Simonato, F. (2023). Big data analytics in healthcare: exploring the role of machine learning in predicting patient outcomes and improving healthcare delivery. International Journal of Computations Information and Manufacturing (Ijcim), 3(1), 1-9. https://doi.org/10.54489/ijcim.v3i1.235
Soyege, O. S., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Nwokedi, C. N., Mbata, A. O., & Iguma, D. R. (2025). Building and maintaining community relationships: The impact on healthcare service delivery. International Journal of Applied Research in Social Sciences, 10(3), 1-15. https://doi.org/10.51594/ijarss.v7i1.
Soyege, O. S., Nwokedi, C. N., Balogun, O. D., Mustapha, A. Y., Tomoh, B. O., Mbata, A. O., & Iguma, D. R. (2024). Big data analytics and artificial intelligence in healthcare: Revolutionizing patient care and clinical outcomes. International Journal of Scientific Research in Science and Technology, 11(6), 1048-1060. https://doi.org/10.32628/IJSRST25121245
Soyege, O. S., Nwokedi, C. N., Tomoh, B. O., Mustapha, A. Y., Mbata, A. O., Balogun, O. D., & Forkuo, A. Y. (2024). Comprehensive review of healthcare innovations in enhancing patient outcomes through advanced pharmacy practices. International Journal of Scientific Research in Science, Engineering and Technology, 11(6), 425-437. https://doi.org/10.32628/IJSERSET242434
Tak, A. (2024). Population health management: leveraging it for better patient outcome’s. International Journal of Health Sciences, 7(2), 53-67. https://doi.org/10.47941/ijhs.1797
Temedie-Asogwa, T., Atta, J. A., Al Zoubi, M. A. M., & Amafah, J. (2024). Economic Impact of Early Detection Programs for Cardiovascular Disease.
Thakur, R. (2024). Explainable ai: developing interpretable deep learning models for medical diagnosis. International Journal for Multidisciplinary Research, 6(4). https://doi.org/10.36948/ijfmr.2024.v06i04.25281
Ueda, D., Kakinuma, T., Fujita, S., Kamagata, K., Fushimi, Y., Ito, R., … & Naganawa, S. (2023). Fairness of artificial intelligence in healthcare: review and recommendations. Japanese Journal of Radiology, 42(1), 3-15. https://doi.org/10.1007/s11604-023-01474-3
Ugwuoke, U., Okeke, F., Obi, E. S., Aguele, B., Onyenemezu, K., & Shoham, D. A. (2024). Assessing the relationship between sleep duration and the prevalence of chronic kidney disease among Veterans in the United States. A 2022 BRFSS Cross-Sectional Study.
Upadhyay, U., Gradišek, A., Iqbal, U., Dhar, E., Li, Y., & Syed-Abdul, S. (2023). Call for the responsible artificial intelligence in the healthcare. BMJ Health & Care Informatics, 30(1), e100920. https://doi.org/10.1136/bmjhci-2023-100920
Uwumiro, F., Anighoro, S. O., Ajiboye, A., Ndulue, C. C., God-dowell, O. O., Obi, E. S., ... & Ogochukwu, O. (2024). Thirty-Day Readmissions After Hospitalization for Psoriatic Arthritis. Cureus, 16(5).
Uwumiro, F., Bojerenu, M. M., Obijuru, C. N., Osiogo, E. O., Ufuah, O. D., Obi, E. S., Okpujie, V., Nebuwa, C. P., Osemwota, O. F., Njoku, J. C., Makata, K. C., & Abesin, O. (2024). Rates and predictors of contrast-associated acute kidney injury following coronary angiography and intervention, 2017–2020 U.S. hospitalizations. SSRN. https://doi.org/10.2139/ssrn.4793659
Uwumiro, F., Nebuwa, C., Nwevo, C. O., Okpujie, V., Osemwota, O., Obi, E. S., ... & Ekeh, C. N. (2023). Cardiovascular Event Predictors in Hospitalized Chronic Kidney Disease (CKD) Patients: A Nationwide Inpatient Sample Analysis. Cureus, 15(10).
Vallée "Digital Twin for Healthcare Systems" Frontiers in Digital Health (2023) doi:10.3389/fdgth.2023.1253050.
Veer, S., Riste, L., Cheraghi‐Sohi, S., Phipps, D., Tully, M., Bozentko, K., … & Peek, N. (2021). Trading off accuracy and explainability in ai decision-making: findings from 2 citizens’ juries. Journal of the American Medical Informatics Association, 28(10), 2128-2138. https://doi.org/10.1093/jamia/ocab127
Wan, T., Matthews, S., Luh, H., Zeng, Y., Wang, Z., & Yang, L. (2022). A proposed multi-criteria optimization approach to enhance clinical outcomes evaluation for diabetes care: a commentary. Health Services Research and Managerial Epidemiology, 9. https://doi.org/10.1177/23333928221089125
Wang, D., Feng, L., Ye, J., Zou, J., & Zheng, Y. (2023). Accelerating the integration of chatgpt and other large‐scale ai models into biomedical research and healthcare. Medcomm – Future Medicine, 2(2). https://doi.org/10.1002/mef2.43
Wang, W., Chen, L., Xiong, M., & Wang, Y. (2021). Accelerating ai adoption with responsible ai signals and employee engagement mechanisms in health care. Information Systems Frontiers, 25(6), 2239-2256. https://doi.org/10.1007/s10796-021-10154-4
Williamson, S. and Prybutok, V. (2024). Balancing privacy and progress: a review of privacy challenges, systemic oversight, and patient perceptions in ai-driven healthcare. Applied Sciences, 14(2), 675. https://doi.org/10.3390/app14020675
Žlahtič, B., Završnik, J., Kokol, P., Vošner, H., Sobotkiewicz, N., Schaubach, B., … & Kirbiš, S. (2024). Trusting ai made decisions in healthcare by making them explainable. Science Progress, 107(3). https://doi.org/10.1177/00368504241266573
Zouo, S. J. C., & Olamijuwon, J. (2024). Financial data analytics in healthcare: A review of approaches to improve efficiency and reduce costs. Open Access Research Journal of Science and Technology, 12(2), 010–019. http://oarjst.com/content/financial-data-analytics-healthcare-review-approaches-improve-efficiency-and-reduce-costs
Zouo, S. J. C., & Olamijuwon, J. (2024). The intersection of financial modeling and public health: A conceptual exploration of cost-effective healthcare delivery. Finance & Accounting Research Journal, 6(11), 2108-2119. https://www.fepbl.com/index.php/farj/article/view/1699