Revolutionizing medical research with artificial intelligence: opportunities, challenges, and strategies: a review

Anas Mohammed Abudasir; Abdullah Saeed; Abdulrahman Bin Saeed; Abdulaziz Mohammed Abudasir; Ali Yahya Alhayani; Khalid Saeed Aldlham; Ghassan E. Mustafa Ahmed; Razan Abdullah Alqahtani

doi:10.18203/2320-6012.ijrms20250708

Authors

Anas Mohammed Abudasir King Khalid university, Abha, KSA
Abdullah Saeed Epidemiology and Public Health Ministry of Health, Abha, KSA
Abdulrahman Bin Saeed Public Health Department, MOH, Abha, KSA
Abdulaziz Mohammed Abudasir King Khalid University, Abha, KSA
Ali Yahya Alhayani King Khalid University, Abha, KSA
Khalid Saeed Aldlham King Khalid University, Abha, KSA
Ghassan E. Mustafa Ahmed University of Khartoum, Sudan https://orcid.org/0000-0002-0258-6282
Razan Abdullah Alqahtani Batterjee Medical College, Abha, KSA

DOI:

https://doi.org/10.18203/2320-6012.ijrms20250708

Keywords:

Artificial intelligence, Bioinformatics, Medical research, Trials

Abstract

This article provides an in-depth exploration of the growing role of artificial intelligence (AI) in medical research, identifying potential applications, key case studies, challenges, strategies for implementation, and future perspectives. AI presents immense opportunities to revolutionize medical research, offering tools for efficient data analysis, accurate prediction of outcomes, and enhanced research efficiency. Specific areas such as genomics, drug discovery, clinical trials, and epidemiology can especially benefit from AI's application, as evidenced by various case studies. However, the journey towards full AI integration in medical research is not without obstacles. Data privacy issues, the necessity for specialized knowledge, rigorous validation of AI models, and algorithm interpretability emerge as significant hurdles. Moreover, ethical considerations, such as the risk of bias in AI algorithms, add another layer of complexity. Realizing these challenges demands ongoing innovation, research, and collaboration across various stakeholders. AI's intersection with medical research heralds a new era of potential scientific discoveries and improved patient outcomes. The article calls for a joint effort from researchers, practitioners, and policymakers to embrace this potential, navigate the challenges, and shape a future where AI serves as an invaluable tool in the pursuit of improved healthcare for all.

Metrics

Metrics Loading ...

References

Choi K, Gitelman Y, Asch D. Artificial intelligence in health care: Anticipating challenges to ethics, privacy, and bias. Penn Bioethics J. 2022;8(2):1-5.

Rajkomar A, Dean J, Kohane I. Machine learning in medicine. N Eng J Med. 2023;378:1347-58. DOI: https://doi.org/10.1056/NEJMra1814259

Topol E. High-performance medicine: the convergence of human and artificial intelligence. Nature Med. 2023;25:44-56. DOI: https://doi.org/10.1038/s41591-018-0300-7

Verghese A, Shah NH, Harrington RA. What this computer needs is a physician: humanism and artificial intelligence. JAMA. 2022;323(1):29-30.

Parikh RB, Teeple S, Navathe AS. Addressing bias in artificial intelligence in health care. JAMA. 2021;322(24):2377-8. DOI: https://doi.org/10.1001/jama.2019.18058

Beam AL, Kohane IS. Big data and machine learning in health care. JAMA. 2023;319(13):1317-8. DOI: https://doi.org/10.1001/jama.2017.18391

Esteva A, Kuprel B, Novoa RA. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2022;542(7639):115-8. DOI: https://doi.org/10.1038/nature21056

Long E, Lin H, Liu Z, Wu X, Wang L, Jiang J, et al. An artificial intelligence platform for the multihospital collaborative management of congenital cataracts. Nature Biomed Engineering. 2022;1:0024. DOI: https://doi.org/10.1038/s41551-016-0024

Blanco-González A, Cabezón A, Seco-González A, Conde-Torres D, Antelo-Riveiro P, Piñeiro Á, et al. The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies. Pharmaceuticals (Basel). 2023;16(6):891. DOI: https://doi.org/10.3390/ph16060891

Chakraborty C, Bhattacharya M, Dhama K, Agoramoorthy G. Artificial intelligence-enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period. Int J Surg. 2023;109(5):1535-8. DOI: https://doi.org/10.1097/JS9.0000000000000088

Vaishya R, Javaid M, Khan IH, Haleem A. Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes Metab Syndr. 2020;14(4):337-9. DOI: https://doi.org/10.1016/j.dsx.2020.04.012

Nanni L, Brahnam S, Lumini A. A local approach based on a Local Neural Network for predicting the progression of Alzheimer's disease. Neurocomputing. 2022;237:26-34.

Kooi T, Litjens G, van Ginneken B, Gubern-Merida A, Sanchez CI, Mann R, et al. Large scale deep learning for computer aided detection of mammographic lesions. Med Image Analysis. 2023;35:303-12. DOI: https://doi.org/10.1016/j.media.2016.07.007

Nguyen D, Jia X, Sher D, Lin MH, Iqbal Z, Liu H, et al. 3D radiotherapy dose prediction on a head and neck cancer population using deep learning. Med Physics. 2023;45(4):1522-31.

Stokes JM, Yang K, Swanson K, Jin W, Cubillos-Ruiz A, Donghia NM, et al. A Deep Learning Approach to Antibiotic Discovery. Cell. 2023;180(4):688-702. DOI: https://doi.org/10.1016/j.cell.2020.01.021

Kim HY. A Case Report on Ground-Level Alternobaric Vertigo Due to Eustachian Tube Dysfunction with the Assistance of Conversational Generative Pre-trained Transformer (ChatGPT). Cureus. 2023;15(3):e36830. DOI: https://doi.org/10.7759/cureus.36830

Liu J, Wang C, Liu S. Utility of ChatGPT in Clinical Practice. J Med Internet Res. 2023;25:e48568. DOI: https://doi.org/10.2196/48568

Grewal H, Dhillon G, Monga V, Sharma P, Buddhavarapu VS, Sidhu G, et al. Radiology Gets Chatty: The ChatGPT Saga Unfolds. Cureus. 2023;15(6):e40135. DOI: https://doi.org/10.7759/cureus.40135

Rao A, Kim J, Kamineni M, Pang M, Lie W, Succi MD. Evaluating ChatGPT as an adjunct for radiologic decision-making. MedRxiv. 2023. DOI: https://doi.org/10.1101/2023.02.02.23285399

Zhou Z. Evaluation of ChatGPT's capabilities in medical report generation. Cureus. 2023;15:0. DOI: https://doi.org/10.7759/cureus.37589

Iftikhar S, Naz I, Zahra A, Zaidi S zainab Y. Report generation of lungs diseases from chest x-ray using NLP. Int J Innov Sci Res Technol. 2021;3:223-33. DOI: https://doi.org/10.33411/IJIST/2021030518

Wiens J, Saria S, Sendak M, Ghassemi M, Liu VX, Doshi-Velez F, Jung K, et al. Do no harm: a roadmap for responsible machine learning for health care. Nature Med. 2022;25:1337-40. DOI: https://doi.org/10.1038/s41591-019-0548-6

Price WN, Gerke S. AI in Health Care: Anticipating Challenges to Ethics, Privacy, and Bias. Penn Bioethics J. 2023;9(1):10-5.

Obermeyer Z, Powers B, Vogeli C, Mullainathan S. Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2023;366(6464):447-53. DOI: https://doi.org/10.1126/science.aax2342

Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data. JAMA Internal Med. 2023;178(11):1544-7. DOI: https://doi.org/10.1001/jamainternmed.2018.3763

Vayena E, Blasimme A, Cohen IG. Machine learning in medicine: Addressing ethical challenges. PLoS Med. 2022;15(11):e1002689. DOI: https://doi.org/10.1371/journal.pmed.1002689

Panch T, Pearson-Stuttard J, Greaves F, Atun R. Artificial intelligence: opportunities and implications for the health workforce. The Lancet Digital Health. 2022;1(2):e13-4. DOI: https://doi.org/10.1016/S2589-7500(19)30002-0

Nsoesie EO. Evaluating artificial intelligence applications in clinical settings. JAMA Netw Open. 2018;1(5):e182658 DOI: https://doi.org/10.1001/jamanetworkopen.2018.2658

Nundy S, Hodgkins ML. The application of AI to augment physicians and reduce burnout. Health Affairs Blog. Available at: https://www.healthaffairs.org/do/10.1377/hblog20180914.711688/full/. Accessed on 18 December 2024.

AiCure NIH expects AiCure Technologies’s new adherence monitoring platform to have “a significant impact widespread application in research and in care.” Press release. Available at: https://aicure.com/nih-expects-aicure-technologiess-new-adherence-monitoring-platform-to-have-a-significant-impact-and-widespread-application-in-research-and-in-care/. Accessed on 18 December 2024.