The Role of Artificial Intelligence in Health Care

Authors

  • Victor Owoyele Associate Editor, NJPS
  • Gbonjubola Oyinlola Ogungbangbe
  • Jesutobiloba Oluwasami
  • Patrick Oluwole Abolarin
  • Maryam Tayo Ayinla

DOI:

https://doi.org/10.54548/njps.v39i1.1

Keywords:

Healthcare, Artificial Intelligence, Personalized medicine, Precision medicine,, Disease Diagnosis, Treatment Plans

Abstract

Artificial intelligence (AI) plays a leading role in transmuting the field of healthcare. Numerous aspects of AI have been incorporated into the healthcare delivery system. For instance, in disease diagnosis, the practice of personalised treatment plans and precision medicine are AI-dependent. This review gives a widespread role of AI in healthcare, with a focus on applications, and challenges. Deep brain stimulation, statistical analysis, machine learning, and deep learning are a few examples of AI-powered technologies that have contributed immensely to biomedical research and medical imaging advancement. Moreover, AI algorithms are pivotal in genomics research, easing the identification of genetic markers related to disease vulnerability and treatment reaction, thereby aiding the practice of precision medicine. Apart from diagnosis and treatment strategies, AI assists in healthcare management and resource optimization, along with the discovery and therapy of drugs. Forecasting of disease outbreaks, effective allocation of hospital resources, and management of patient traffic rely mostly on predictive analytics driven by AI. Again, AI-powered virtual health assistance, telemedicine has aided patient appointments and support, giving real-time support and health recommendations. Although AI algorithms provide outstanding breakthroughs in healthcare, AI adoption is cumbered by numerous dares such as monetary concerns, regulatory hurdles, data privacy fears, and ethical considerations associated with AI applications, such as algorithm bias and transparency. Futuristically, AI application in healthcare holds vast potential, such as early disease detection, drug discovery, and optimization of treatment. Concerted efforts targeted at tackling the prevailing challenges and creating holistic control would be important to tie together the full potential of AI in rejuvenating the healthcare delivery system.

 

 

References

Abdullah, Y. I., Schuman, J. S., Shabsigh, R., Caplan, A., & Al-Aswad, L. A. (2021). Ethics of Artificial Intelligence in Medicine and Ophthalmology. The Asia-Pacific Journal of Ophthalmology, 10(3), 289–298.

Bertsimas, D., Dunn, J., Velmahos, G. C., & Kaafarani, H. M. A. (2018). Surgical Risk Is Not Linear. Annals of Surgery, 268(4), 574–583.

Bhinder, B., Gilvary, C., Madhukar, N. S., & Elemento, O. (2021). Artificial Intelligence in Cancer Research and Precision Medicine. Cancer Discovery, 11(4), 900–915.

Biswal, A. (2024). Top 10 Deep Learning Algorithms You Should Know in 2023. Simplilearn.com. https://www.simplilearn.com/tutorials/deep-learning-tutorial/deep-learning-algorithm

Chiu, Y.-C., Chen, H.-I. H., Zhang, T., Zhang, S., Gorthi, A., Wang, L.-J., Huang, Y., & Chen, Y. (2019). Predicting drug response of tumors from integrated genomic profiles by deep neural networks. BMC Medical Genomics, 12(S1).

Davenport, T., & Kalakota, R. (2019). The Potential for Artificial Intelligence in Healthcare. Future Healthcare Journal, 6(2), 94–98.

Feeny, A. K., Chung, M. K., Madabhushi, A., Attia, Z. I., Cikes, M., Firouznia, M., Friedman, P. A., Kalscheur, M. M., Kapa, S., Narayan, S. M., Noseworthy, P. A., Passman, R. S., Perez, M. V., Peters, N. S., Piccini, J. P., Tarakji, K. G., Thomas, S. A., Trayanova, N. A., Turakhia, M. P., & Wang, P. J. (2020). Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology. Circulation: Arrhythmia and Electrophysiology, 13(8).

Fjelland, R. (2020). Why general artificial intelligence will not be realized. Humanities and Social Sciences Communications, 7(1).

Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., Venugopalan, S., Widner, K., Madams, T., Cuadros, J., Kim, R., Raman, R., Nelson, P. C., Mega, J. L., & Webster, D. R. (2016). Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA, 316(22), 2402.

Gupta, R., Srivastava, D., Sahu, M., Tiwari, S., Ambasta, R. K., & Kumar, P. (2021). Artificial intelligence to deep learning: machine intelligence approach for drug discovery. Molecular Diversity, 25(3), 1–46.

Harrer, S., Shah, P., Antony, B., & Hu, J. (2019). Artificial Intelligence for Clinical Trial Design. Trends in Pharmacological Sciences, 40(8), 577–591.

Hernández-de-Diego, R., Tarazona, S., Martínez-Mira, C., Balzano-Nogueira, L., Furió-Tarí, P., Pappas, G., & Conesa, A. (2018). PaintOmics 3: a web resource for the pathway analysis and visualization of multi-omics data. 46(W1), W503–W509.

Hu, H. P., Niu, Z. J., Bai, Y. P., & Tan, X. H. (2015). Cancer classification based on gene expression using neural networks. Genetics and Molecular Research, 14(4), 17605–17611.

Iorio, F., Knijnenburg, T. A., Vis, D. J., Bignell, G. R., Menden, M. P., Schubert, M., Aben, N., Gonçalves, E., Barthorpe, S., Lightfoot, H., Cokelaer, T., Greninger, P., van Dyk, E., Chang, H., de Silva, H., Heyn, H., Deng, X., Egan, R. K., Liu, Q., & Mironenko, T. (2016). A Landscape of Pharmacogenomic Interactions in Cancer. Cell, 166(3), 740–754.

Janett, R. S., & Yeracaris, P. P. (2020). Electronic Medical Records in the American Health System: Challenges and Lessons Learned. Ciência & Saúde Coletiva, 25(4), 1293–1304.

Jassar, S., Adams, S. J., Zarzeczny, A., & Burbridge, B. E. (2022). The future of artificial intelligence in medicine: Medical-legal considerations for health leaders. Healthcare Management Forum, 35(3), 185–189.

Jiang, F., Jiang, Y., & Zhi, H. (2017). Artificial intelligence in healthcare: past, present and future. Stroke and Vascular Neurology, 2(4), 230–243.

Johannet, P., Coudray, N., Donnelly, D. M., Jour, G., Illa-Bochaca, I., Xia, Y., Johnson, D. B., Wheless, L., Patrinely, J. R., Nomikou, S., Rimm, D. L., Pavlick, A. C., Weber, J. S., Zhong, J., Tsirigos, A., & Osman, I. (2021). Using Machine Learning Algorithms to Predict Immunotherapy Response in Patients with Advanced Melanoma. Clinical Cancer Research, 27(1), 131–140.

Johnson, K. B., Wei, W., Weeraratne, D., Frisse, M. E., Misulis, K., Rhee, K., Zhao, J., & Snowdon, J. L. (2020). Precision Medicine, AI, and the Future of Personalized Health Care. Clinical and Translational Science, 14(1).

Kanade, V. (2022a). What Is General Artificial Intelligence (AI)? Definition, Challenges, and Trends. Spiceworks. https://www.spiceworks.com/tech/artificial-intelligence/articles/what-is-general-ai/

Kanade, V. (2022b). What Is Super Artificial Intelligence (AI)? Definition, Threats, and Trends. Spiceworks. https://www.spiceworks.com/tech/artificial-intelligence/articles/super-artificial-intelligence/

Laskowski, N., & Tucci, L. (2022). What Is Artificial Intelligence (AI)? TechTarget. https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence

Lipkova, J., Chen, R. J., Chen, B., Lu, M. Y., Barbieri, M., Shao, D., Vaidya, A. J., Chen, C., Zhuang, L., Williamson, D. F. K., Shaban, M., Chen, T. Y., & Mahmood, F. (2022). Artificial intelligence for multimodal data integration in oncology. Cancer Cell, 40(10), 1095–1110.

Lund, B., Omame, I., Tijani, S., & Agbaji, D. (2020). Perceptions toward Artificial Intelligence among Academic Library Employees and Alignment with the Diffusion of Innovations’ Adopter Categories. College & Research Libraries, 81(5), 865.

Lutkevich, B. (2022). What is artificial general intelligence (AGI)? - Definition from WhatIs.com. SearchEnterpriseAI. https://www.techtarget.com/searchenterpriseai/definition/artificial-general-intelligence-AGI

McLean, S., Read, G. J. M., Thompson, J., Baber, C., Stanton, N. A., & Salmon, P. M. (2021). The risks associated with Artificial General Intelligence: A systematic review. Journal of Experimental & Theoretical Artificial Intelligence, 35(5), 1–17.

Merriam-Webster. (2023). Definition of health care. Merriam-Webster.com. https://www.merriam-webster.com/dictionary/health%20care

Mitsala, A., Tsalikidis, C., Pitiakoudis, M., Simopoulos, C., & Tsaroucha, A. K. (2021). Artificial Intelligence in Colorectal Cancer Screening, Diagnosis and Treatment. A New Era. Current Oncology, 28(3), 1581–1607.

Mohapatra, S. (2022). Analyzing and Comparing Deep Learning Models. Analytics Vidhya. https://www.analyticsvidhya.com/blog/2022/11/analyzing-and-comparing-deep-learning-models/

Mukhopadhyay, S. C., Suryadevara, N. K., & Nag, A. (2022). Wearable Sensors for Healthcare: Fabrication to Application. Sensors, 22(14), 5137.

National Cancer Institute. (2011). Www.cancer.gov. https://www.cancer.gov/publications/dictionaries/cancer-terms/def/drug-therapyubstance

Newman, T. (2017). Introduction to physiology: History, biological systems, and branches. Www.medicalnewstoday.com. https://www.medicalnewstoday.com/articles/248791

Noorbakhsh-Sabet, N., Zand, R., Zhang, Y., & Abedi, V. (2019). Artificial Intelligence Transforms the Future of Health Care. The American Journal of Medicine, 132(7), 795–801.

Paul, D., Sanap, G., Shenoy, S., Kalyane, D., Kalia, K., & Tekade, R. K. (2020). Artificial intelligence in drug discovery and development. Drug Discovery Today, 26(1). ncbi.

Pereira, J. C., Caffarena, E. R., & dos Santos, C. N. (2016). Boosting Docking-Based Virtual Screening with Deep Learning. Journal of Chemical Information and Modeling, 56(12), 2495–2506.

Pongtriang, P., Rakhab, A., Bian, J., Guo, Y., & Maitree, K. (2023). Challenges in Adopting Artificial Intelligence to Improve Healthcare Systems and Outcomes in Thailand. Healthcare Informatics Research, 29(3), 280–282.

Rajpurkar, P., Chen, E., Banerjee, O., & Topol, E. J. (2022). AI in health and medicine. Nature Medicine, 28(1), 31–38.

Ridley, D. (2022). Sub-Sectors in the Health Care Industry | HSM. Centers.fuqua.duke.edu. https://centers.fuqua.duke.edu/hsm/home/students/career-info/sub-sectors-in-the-health-care-industry/

Saeed, E., Szymkowski, M., Saeed, K., & Mariak, Z. (2019). An Approach to Automatic Hard Exudate Detection in Retina Color Images by a Telemedicine System Based on the d-Eye Sensor and Image Processing Algorithms. Sensors, 19(3), 695.

Samad, M. D., Ulloa, A., Wehner, G. J., Jing, L., Hartzel, D., Good, C. W., Williams, B. A., Haggerty, C. M., & Fornwalt, B. K. (2019). Predicting Survival From Large Echocardiography and Electronic Health Record Datasets. JACC: Cardiovascular Imaging, 12(4), 681–689.

Saqib, M., Sha, Y., & Wang, M. D. (2018). Early Prediction of Sepsis in EMR Records Using Traditional ML Techniques and Deep Learning LSTM Networks. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Schneider, S., Aldington, S. J., Kohner, E. M., Luzio, S., Owens, D. R., Schmidt, V., Schuell, H., & Zahlmann, G. (2005). Quality assurance for diabetic retinopathy telescreening. Diabetic Medicine, 22(6), 794–802.

Sellwood, M. A., Ahmed, M., Segler, M. H., & Brown, N. (2018). Artificial intelligence in drug discovery. Future Medicinal Chemistry, 10(17), 2025–2028.

Shabani, M., & Hojjat-Farsangi, M. (2016). Targeting Receptor Tyrosine Kinases Using Monoclonal Antibodies: The Most Specific Tools for Targeted-Based Cancer Therapy. Current Drug Targets, 17(14), 1687–1703.

Shaw, J., Rudzicz, F., Jamieson, T., & Goldfarb, A. (2019). Artificial Intelligence and the Implementation Challenge. Journal of Medical Internet Research, 21(7), e13659.

Shen, Y.-T., Chen, L., Yue, W.-W., & Xu, H.-X. (2021). Digital Technology-Based Telemedicine for the COVID-19 Pandemic. Frontiers in Medicine, 8.

Song, H., Chen, L., Cui, Y., Li, Q., Wang, Q., Fan, J., Yang, J., & Zhang, L. (2022). Denoising of MR and CT images using cascaded multi-supervision convolutional neural networks with progressive training. Neurocomputing, 469, 354–365.

Spiceworks. (2022). What Is Narrow Artificial Intelligence (AI)? Definition, Challenges, and Best Practices for 2022 | Spiceworks. Spiceworks. https://www.spiceworks.com/tech/artificial-intelligence/articles/what-is-narrow-ai/

Stanfill, M. H., & Marc, D. T. (2019). Health Information Management: Implications of Artificial Intelligence on Healthcare Data and Information Management. Yearbook of Medical Informatics, 28(01), 056–064.

Ting, D. S. W., Pasquale, L. R., Peng, L., Campbell, J. P., Lee, A. Y., Raman, R., Tan, G. S. W., Schmetterer, L., Keane, P. A., & Wong, T. Y. (2018). Artificial intelligence and deep learning in ophthalmology. British Journal of Ophthalmology, 103(2), 167–175.

Vishaal. (2023). Era Of Artificial Superintelligence - What Lies In It for Us? Www.calibraint.com. https://www.calibraint.com/blog/era-of-artificial-superintelligence

Wang, F., & Preininger, A. (2019). AI in Health: State of the Art, Challenges, and Future Directions. Yearbook of Medical Informatics, 28(01), 016–026.

You, Y., Lai, X., Pan, Y., Zheng, H., Vera, J., Liu, S., Deng, S., & Zhang, L. (2022). Artificial intelligence in cancer target identification and drug discovery. Signal Transduction and Targeted Therapy, 7(1).

Zhang, L., & Zhang, S. (2017). Using game theory to investigate the epigenetic control mechanisms of embryo development. Physics of Life Reviews, 20, 140–142.

Zhong, F., Xing, J., Li, X., Liu, X., Fu, Z., Xiong, Z., Lu, D., Wu, X., Zhao, J., Tan, X., Li, F., Luo, X., Li, Z., Chen, K., Zheng, M., & Jiang, H. (2018). Artificial intelligence in drug design. Science China. Life Sciences, 61(10), 1191–1204.

Zhou, Y., Wang, F., Tang, J., Nussinov, R., & Cheng, F. (2020). Artificial intelligence in COVID-19 drug repurposing. The Lancet Digital Health.

Zhu, H. (2019). Big Data and Artificial Intelligence Modeling for Drug Discovery. Annual Review of Pharmacology and Toxicology, 60(1).

Downloads

Published

2025-01-14

Issue

Section

Review Articles

How to Cite

The Role of Artificial Intelligence in Health Care. (2025). Nigerian Journal of Physiological Sciences, 39(1), 1-8. https://doi.org/10.54548/njps.v39i1.1

Similar Articles

1-10 of 142

You may also start an advanced similarity search for this article.