Drawbacks of artificial intelligence and their potential solutions in the healthcare sector.
Open accessAbstract
Artificial intelligence (AI) has the potential to make substantial progress toward the goal of making healthcare more personalized, predictive, preventative, and interactive. We believe AI will continue its present path and ultimately become a mature and effective tool for the healthcare sector. Besides this AI-based systems raise concerns regarding data security and privacy. Because health records are important and vulnerable, hackers often target them during data breaches. The absence of standard guidelines for the moral use of AI and ML in healthcare has only served to worsen the situation. There is debate about how far artificial intelligence (AI) may be utilized ethically in healthcare settings since there are no universal guidelines for its use. Therefore, maintaining the confidentiality of medical records is crucial. This study enlightens the possible drawbacks of AI in the implementation of healthcare sector and their solutions to overcome these situations.Graphical abstract
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Cites
LeCun, Y., Bengio, Y., & Hinton, G. (2015) · Nature · doi:10.1038/nature14539 · Cited by 84,126 · see citing works
Damschroder, L. J., Aron, D. C., Keith, R. E., Kirsh, S. R., Alexander, J. A., & Lowery, J. C. (2009) · Implementation Science · doi:10.1186/1748-5908-4-50 · Cited by 14,496 · see citing works
A guide to deep learning in healthcare
Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0316-z · Cited by 5,312 · see citing works
Artificial intelligence in healthcare: past, present and future
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., Wang, Y., Dong, Q., Shen, H., & Wang, Y. (2017) · Stroke and Vascular Neurology · doi:10.1136/svn-2017-000101 · Cited by 4,837 · see citing works
The potential for artificial intelligence in healthcare
Davenport, T., & Kalakota, R. (2019) · Future Healthcare Journal · doi:10.7861/futurehosp.6-2-94 · Cited by 3,800 · see citing works
The practical implementation of artificial intelligence technologies in medicine
He, J., Baxter, S. L., Xu, J., Xu, J., Zhou, X., & Zhang, K. (2019) · Nature Medicine · doi:10.1038/s41591-018-0307-0 · Cited by 2,246 · see citing works
Probabilistic machine learning and artificial intelligence
Ghahramani, Z. (2015) · Nature · doi:10.1038/nature14541 · Cited by 1,995 · see citing works
The Ethics of AI Ethics: An Evaluation of Guidelines
Hagendorff, T. (2020) · Minds and Machines · doi:10.1007/s11023-020-09517-8 · Cited by 1,911 · see citing works
Governing artificial intelligence: ethical, legal and technical opportunities and challenges
Cath, C. (2018) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2018.0080 · Cited by 745 · cited 1× · see citing works
“To overcome these hindrances, possible solutions have been suggested to deal with the issues of fairness, accountability, and transparency through the implementation of ethical governance, model explain ability, model inter-pretability, and ethical auditing [29].”
Artificial intelligence for clinical trial design
Harrer, S., Shah, P., Antony, B., & Hu, J. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.05.005 · Cited by 672 · see citing works
Advancing drug discovery via artificial intelligence
Chan, H. C. S., Shan, H., Dahoun, T., Vogel, H., & Yuan, S. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.06.004 · Cited by 654 · see citing works
Introducing artificial intelligence training in medical education
Paranjape, K., Schinkel, M., Nannan Panday, R., Car, J., & Nanayakkara, P. (2019) · JMIR Medical Education · doi:10.2196/16048 · Cited by 634 · see citing works
Opening the black box: low-dimensional dynamics in high-dimensional recurrent neural networks
Sussillo, D., & Barak, O. (2013) · Neural Computation · doi:10.1162/neco_a_00409 · Cited by 575 · see citing works
Pyzer-Knapp, E. O., Pitera, J. W., Staar, P. W. J., Takeda, S., Laino, T., Sanders, D. P., Sexton, J., Smith, J. R., & Curioni, A. (2022) · npj Computational Materials · doi:10.1038/s41524-022-00765-z · Cited by 465 · see citing works
A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia
Lee, S., Çelik, S., Logsdon, B. A., Lundberg, S., Martins, T. J., Oehler, V. G., Estey, E. H., Miller, C. P., Chien, S. S., Dai, J., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-02465-5 · Cited by 332 · see citing works
Ethical dimensions of using artificial intelligence in health care
(2019) · AMA Journal of Ethics · doi:10.1001/amajethics.2019.121 · Cited by 328 · see citing works
Fernandes, M. P., Vieira, S. M., Leite, F., Palos, C., Finkelstein, S. N., & Sousa, J. M. C. (2019) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2019.101762 · Cited by 314 · see citing works
Artificial intelligence education programs for health care professionals: Scoping review
Charow, R., Jeyakumar, T., Younus, S., Dolatabadi, E., Salhia, M., Al-Mouaswas, D., Anderson, M., Balakumar, S., Clare, M., Dhalla, A., et al. (2021) · JMIR Medical Education · doi:10.2196/31043 · Cited by 291 · see citing works
Systematic Review of Economic Impact Studies of Artificial Intelligence in Health Care
Wolff, J., Pauling, J. K., Keck, A., & Baumbach, J. (2019) · Journal of Medical Internet Research · doi:10.2196/16866 · Cited by 277 · see citing works
Synthesizing electronic health records using improved generative adversarial networks
Baowaly, M. K., Lin, C.-C., Liu, C.-L., & Chen, K.-T. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy142 · Cited by 273 · see citing works
Towards Bayesian Deep Learning: A Framework and Some Existing Methods
Wang, H., & Yeung, D. (2016) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2016.2606428 · Cited by 254 · see citing works
What do medical students actually need to know about artificial intelligence?
McCoy, L. G., Nagaraj, S., Morgado, F., Harish, V., Das, S., & Celi, L. A. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-0294-7 · Cited by 240 · see citing works
Artificial intelligence in healthcare: a critical analysis of the legal and ethical implications
Schönberger, D. (2019) · International Journal of Law and Information Technology · doi:10.1093/ijlit/eaz004 · Cited by 230 · see citing works
Gama, F., Tyskbo, D., Nygren, J., Barlow, J., Reed, J., & Svedberg, P. (2022) · Journal of Medical Internet Research · doi:10.2196/32215 · Cited by 216 · see citing works
Schmidt-Erfurth, U. M., Bogunović, H., Sadeghipour, A., Schlegl, T., Langs, G., Gerendas, B. S., Osborne, A. R., & Waldstein, S. M. (2017) · Ophthalmology Retina · doi:10.1016/j.oret.2017.03.015 · Cited by 200 · see citing works
Denti, L., & Hemlin, S. (2012) · International Journal of Innovation Management · doi:10.1142/s1363919612400075 · Cited by 194 · see citing works
Using artificial intelligence to improve hospital inpatient care
Neill, D. B. (2013) · IEEE Intelligent Systems · doi:10.1109/mis.2013.51 · Cited by 177 · see citing works
Simple rules for evidence translation in complex systems: A qualitative study
Reed, J. E., Howe, C., Doyle, C., & Bell, D. (2018) · BMC Medicine · doi:10.1186/s12916-018-1076-9 · Cited by 173 · see citing works
Wiljer, D., & Hakim, Z. (2019) · Journal of Medical Imaging and Radiation Sciences · doi:10.1016/j.jmir.2019.09.010 · Cited by 170 · see citing works
Criteria for the use of omics-based predictors in clinical trials: explanation and elaboration
McShane, L. M., Cavenagh, M. M., Lively, T., Eberhard, D. A., Bigbee, W. L., Williams, P. M., Mesirov, J. P., Polley, M. C., Kim, K. Y., Tricoli, J. V., et al. (2013) · BMC Medicine · doi:10.1186/1741-7015-11-220 · Cited by 140 · see citing works
Alami, H., Lehoux, P., Denis, J., Motulsky, A., Petitgand, C., Savoldelli, M., Rouquet, R., Gagnon, M., Roy, D. A., & Fortin, J. (2020) · Journal of Health Organization and Management · doi:10.1108/jhom-03-2020-0074 · Cited by 140 · see citing works
Artificial Intelligence in Clinical Health Care Applications: Viewpoint
van Hartskamp, M., Consoli, S., Verhaegh, W., Petković, M., & van de Stolpe, A. (2019) · Interactive Journal of Medical Research · doi:10.2196/12100 · Cited by 126 · see citing works
Artificial Intelligence and Public PolicyPreprint
Thierer, A. D., Castillo, A., & Russell, R. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3021135 · Cited by 108 · see citing works
Verhaegh, W., van Ooijen, H., de Inda, M. A., Hatzis, P., Versteeg, R., Smid, M., Martens, J. W. M., Foekens, J. A., van de Wiel, P., Clevers, H. C., et al. (2014) · Cancer Research · doi:10.1158/0008-5472.can-13-2515 · Cited by 91 · see citing works
Cruciger, O., Schildhauer, T. A., Meindl, R. C., Tegenthoff, M., Schwenkreis, P., Çıtak, M., & Aach, M. (2014) · Disability and Rehabilitation Assistive Technology · doi:10.3109/17483107.2014.981875 · Cited by 84 · see citing works
How Should AI Be Developed, Validated, and Implemented in Patient Care?
Anderson, M., & Anderson, S. (2019) · The AMA Journal of Ethic · doi:10.1001/amajethics.2019.125 · Cited by 73 · see citing works
Lee, T. T., & Kesselheim, A. S. (2018) · Annals of Internal Medicine · doi:10.7326/m17-2715 · Cited by 62 · see citing works
Use of Bayesian statistics in drug development: Advantages and challenges
Gupta, S. K. (2012) · International Journal of Applied and Basic Medical Research · doi:10.4103/2229-516x.96789 · Cited by 60 · see citing works
van de Stolpe, A., Holtzer, L., van Ooijen, H., de Inda, M. A., & Verhaegh, W. (2019) · Scientific Reports · doi:10.1038/s41598-018-38179-x · Cited by 60 · see citing works
Artificial Intelligence: A Novel Approach for Drug Discovery
Díaz, Ó., Dalton, J. A. R., & Giraldo, J. (2019) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2019.06.005 · Cited by 59 · see citing works
van Ooijen, H., Hornsveld, M., Veen, C. D.-D., Velter, R., Dou, M., Verhaegh, W., Burgering, B. M. T., & van de Stolpe, A. (2018) · American Journal Of Pathology · doi:10.1016/j.ajpath.2018.05.020 · Cited by 55 · see citing works
Just data? Solidarity and justice in data-driven medicine
Hummel, P., & Braun, M. (2020) · Life Sciences Society and Policy · doi:10.1186/s40504-020-00101-7 · Cited by 53 · see citing works
Hörnle, J. (2019) · International Journal of Law and Information Technology · doi:10.1093/ijlit/eaz002 · Cited by 43 · see citing works
Zarringhalam, K., EnayetAllah, A. E., Reddy, P. S., & Ziemek, D. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu272 · Cited by 26 · see citing works
De-Health: All Your Online Health Information Are Belong to Us
Ji, S., Gu, Q., Weng, H., Liu, Q., Zhou, P., Chen, J., Li, Z., Beyah, R., & Wang, T. (2020) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde48307.2020.00143 · Cited by 19 · see citing works
Merging weighted SVMs for parallel incremental learning
Zhu, L., Ikeda, K., Pang, S., Ban, T., & Sarrafzadeh, A. (2018) · Neural Networks · doi:10.1016/j.neunet.2018.01.001 · Cited by 18 · see citing works
Innovative human-specific investigational approaches to autoimmune disease
van de Stolpe, A., & Kauffmann, R. H. (2015) · RSC Advances · doi:10.1039/c4ra15794j · Cited by 15 · see citing works
Molecular causes of transcriptional response: a Bayesian prior knowledge approach
Zarringhalam, K., EnayetAllah, A. E., Gutteridge, A., Sidders, B. S., & Ziemek, D. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt557 · Cited by 14 · see citing works
Residents’ Introduction to Comparative Effectiveness Research and Big Data Analytics
Kang, S. K., Lee, C. I., Pandharipande, P. V., Sanelli, P. C., & Recht, M. P. (2017) · Journal of the American College of Radiology · doi:10.1016/j.jacr.2016.10.032 · Cited by 13 · see citing works
Khan, B., Kumar, S., Sanbhal, N., Abdullah, S., Hussain, J. S., Chowdhry, N. P., Ansari, A. Q., & Surahio, M. M. (2022) · Biomedical Materials & Devices · doi:10.1007/s44174-022-00014-3 · Cited by 7 · see citing works
Self-citationKhan, B., & Kumar, S. (2022) · Research Square · doi:10.21203/rs.3.rs-2156625/v1 · Cited by 5 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 4
- [4]J. Habermann, Psychological impacts of COVID-19 and preventive strategies: A review. (2021).
- [6]A. Holzinger, C. Biemann, C. S. Pattichis, D. B. Kell, What do we need to build explainable AI systems for the medical domain? (2017). https://arXiv.Org/:1712.09923.
- [54]Wang H Yeung D-Y Towards Bayesian deep learning: a framework and some existing methods IEEE Trans. Knowl. Data Eng. 2016 28 3395 3408 10.1109/TKDE.2016.2606428 · DOI
- [60]Miley D Machado LB Condo C Jergens AE Yoon K-J Pandey S Video capsule endoscopy and ingestible electronics: emerging trends in sensors, circuits, materials, telemetry, optics, and rapid reading software Adv. Devices Instrum. 2021 2021 1 30 10.3433/2021/9854040 · DOI
Cited by
Sorted by citations
A Review of the Role of Artificial Intelligence in Healthcare
Al Kuwaiti, A., Nazer, K., Al-Reedy, A., Al-Shehri, S., Al-Muhanna, A., Subbarayalu, A. V., Al Muhanna, D., & Al-Muhanna, F. A. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13060951 · Cited by 915 · see citing works
Esmaeilzadeh, P. (2024) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2024.102861 · Cited by 420 · see citing works
Artificial intelligence in clinical medicine: catalyzing a sustainable global healthcare paradigm
Krishnan, G., Singh, S., Pathania, M., Gosavi, S., Abhishek, S., Parchani, A., & Dhar, M. (2023) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2023.1227091 · Cited by 326 · see citing works
Faiyazuddin, M., Rahman, S. J. Q., Anand, G., Siddiqui, R. K., Mehta, R., Khatib, M. N., Gaidhane, S., Zahiruddin, Q. S., Hussain, A., & Sah, R. (2025) · Health Science Reports · doi:10.1002/hsr2.70312 · Cited by 299 · see citing works
Large Language Models for Chatbot Health Advice Studies: A Systematic Review
Huo, B., Boyle, A., Marfo, N., Tangamornsuksan, W., Steen, J. P., McKechnie, T., Lee, Y., Mayol, J., Antoniou, S. A., Thirunavukarasu, A. J., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.57879 · Cited by 283 · see citing works
Artificial intelligence in healthcare delivery: Prospects and pitfalls
Olawade, D. B., David-Olawade, A. C., Wada, O. Z., Asaolu, A. J., Adereni, T., & Ling, J. (2024) · Journal of Medicine Surgery and Public Health · doi:10.1016/j.glmedi.2024.100108 · Cited by 214 · see citing works
Gala, D., Behl, H., Shah, M., & Makaryus, A. N. (2024) · Healthcare · doi:10.3390/healthcare12040481 · Cited by 206 · see citing works
Zuhair, V., Babar, A., Ali, R., Oduoye, M. O., Noor, Z., Chris, K., Okon, I. I., & Rehman, L. U. (2024) · Journal of Primary Care & Community Health · doi:10.1177/21501319241245847 · Cited by 197 · see citing works
Yelne, S., Chaudhary, M., Dod, K., Sayyad, A., & Sharma, R. (2023) · Cureus · doi:10.7759/cureus.49252 · Cited by 190 · see citing works
Theranostics and artificial intelligence: new frontiers in personalized medicine
Bilgin, G. B., Bilgin, C., Burkett, B. J., Orme, J. J., Childs, D. S., Thorpe, M. P., Halfdanarson, T. R., Johnson, G. B., Kendi, A. T., & Sartor, O. A. (2024) · Theranostics · doi:10.7150/thno.94788 · Cited by 151 · see citing works
Security Implications of AI Chatbots in Health Care
Li, J. (2023) · Journal of Medical Internet Research · doi:10.2196/47551 · Cited by 148 · see citing works
Exploring student perspectives on generative artificial intelligence in higher education learning
Baidoo-Anu, D., Asamoah, D., Amoako, I., & Mahama, I. (2024) · Discover Education · doi:10.1007/s44217-024-00173-z · Cited by 136 · see citing works
Parvin, N., Joo, S., Jung, J. H., & Mandal, T. K. (2025) · Nanomaterials · doi:10.3390/nano15120895 · Cited by 130 · see citing works
Pavuluri, S., Sangal, R., Sather, J., & Taylor, R. A. (2024) · BMJ Health & Care Informatics · doi:10.1136/bmjhci-2024-101120 · Cited by 129 · see citing works
Ng, F. Y. C., Thirunavukarasu, A. J., Cheng, H., Tan, T. F., Gutierrez, L., Lan, Y., Ong, J. C. L., Chong, Y. S., Ngiam, K. Y., Ho, D., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101230 · Cited by 113 · see citing works
Reimagining Healthcare: Unleashing the Power of Artificial Intelligence in Medicine
Iqbal, J., Jaimes, D. C. C., Makineni, P., Subramani, S., Hemaida, S., Thugu, T. R., Butt, A. N., Sikto, J. T., Kaur, P., Lak, M. A., et al. (2023) · Cureus · doi:10.7759/cureus.44658 · Cited by 109 · see citing works
Exploring the role of AI in education
Nguyen, N. D. (2023) · London Journal of Social Sciences · doi:10.31039/ljss.2023.6.108 · Cited by 101 · see citing works
Qiu, X., Li, H., Steeg, G. V., & Godzik, A. (2024) · Biomolecules · doi:10.3390/biom14030339 · Cited by 100 · see citing works
Rahman, M. A., Victoros, E., Ernest, J., Davis, R., Shanjana, Y., & Islam, M. R. (2024) · Clinical Pathology · doi:10.1177/2632010x241226887 · Cited by 93 · see citing works
Prompt Engineering in Healthcare
Patil, R., Heston, T. F., & Bhuse, V. (2024) · Electronics · doi:10.3390/electronics13152961 · Cited by 93 · see citing works
Advancements in wearable sensors for cardiovascular disease detection for health monitoring
Khan, B., Riaz, Z., Ahmad, R. U. S., & Khoo, B. L. (2024) · Materials Science and Engineering R Reports · doi:10.1016/j.mser.2024.100804 · Cited by 87 · see citing works
Self-citationSallam, M., Barakat, M. M., & Sallam, M. (2023) · Cureus · doi:10.7759/cureus.49373 · Cited by 80 · see citing works
Babu, A., & Joseph, A. P. (2024) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1378904 · Cited by 77 · see citing works
Kulkarni, P., Paudel, N., Magar, S., Santilli, M. F., Kashyap, S., Baranwal, A. K., Zamboni, P., Vasavada, P., Katiyar, A., & Singh, A. V. (2023) · Biomedical Materials & Devices · doi:10.1007/s44174-023-00087-8 · Cited by 76 · see citing works
Botha, N. N., Segbedzi, C. E., Dumahasi, V. K., Maneen, S., Kodom, R. V., Tsedze, I. S., Akoto, L. A., Atsu, F. S., Lasim, O. U., & Ansah, E. W. (2024) · Archives of Public Health · doi:10.1186/s13690-024-01414-1 · Cited by 75 · see citing works
Artificial Intelligence in Cardiovascular Care—Part 2: Applications
Jain, S. S., Elias, P., Poterucha, T., Randazzo, M., Lopez Jimenez, F., Khera, R., Perez, M., Ouyang, D., Pirruccello, J., Salerno, M., et al. (2024) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2024.03.401 · Cited by 74 · see citing works
ШТУЧНИЙ ІНТЕЛЕКТ У СУЧАСНІЙ ОСВІТІ: ПЕРСПЕКТИВИ ЗАСТОСУВАННЯ ТА ВИКЛИКИ
Kutsak, L. (2025) · Modern Information Technologies and Innovation Methodologies of Education in Professional Training Methodology Theory Experience Problems · doi:10.31652/2412-1142-2024-74-27-37 · Cited by 73 · see citing works
Can Artificial Intelligence Replace the Unique Nursing Role?
Mohanasundari, S. K., Kalpana, M., Madhusudhan, U., Vasanthkumar, K., B, R., Singh, R., Vashishtha, N., & Bhatia, V. (2023) · Cureus · doi:10.7759/cureus.51150 · Cited by 71 · see citing works
Mohajer-Bastami, A., Moin, S., Ahmad, S., Ahmed, A. R., Pouwels, S., Hajibandeh, S., Yang, W., Parmar, C. D., Kermansaravi, M., Khalil, M., et al. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1644041 · Cited by 70 · see citing works
Artificial Intelligence and Occupational Health and Safety, Benefits and Drawbacks
El-Helaly, M. (2024) · La Medicina del Lavoro · doi:10.23749/mdl.v115i2.15835 · Cited by 68 · see citing works
Özduran, E., Akkoç, İ., Büyükçoban, S., Erkin, Y., & Hancı, V. (2025) · Medicine · doi:10.1097/md.0000000000041780 · Cited by 65 · see citing works
Artificial Intelligence Applications in Smart Healthcare: A Survey
Gao, X., He, P., Zhou, Y. X., & Qin, X. (2024) · Future Internet · doi:10.3390/fi16090308 · Cited by 65 · see citing works
Mapari, S. A., Shrivastava, D., Dave, A., Bedi, G. N., Gupta, A., Sachani, P., Kasat, P. R., & Pradeep, U. (2024) · Cureus · doi:10.7759/cureus.69555 · Cited by 62 · see citing works
The Crucial Role of Interdisciplinary Conferences in Advancing Explainable AI in Healthcare
Patel, A., Gu, Q., Esper, R. N., Maeser, D., & Maeser, N. (2024) · BioMedInformatics · doi:10.3390/biomedinformatics4020075 · Cited by 61 · see citing works
Artificial intelligence in endocrinology: a comprehensive review
Giorgini, F., Dalmazi, G. D., & Diciotti, S. (2023) · Journal of Endocrinological Investigation · doi:10.1007/s40618-023-02235-9 · Cited by 58 · see citing works
The use of AI in mental health services to support decision-making: scoping review
Auf, H., Svedberg, P., Nygren, J., Nair, M., & Lundgren, L. E. (2025) · Journal of Medical Internet Research · doi:10.2196/63548 · Cited by 56 · see citing works
Al Hadithy, Z. A., Al Lawati, A., Al-Zadjali, R., & Al Sinawi, H. (2023) · Cureus · doi:10.7759/cureus.44887 · Cited by 55 · see citing works
Temel, M. H., Erden, Y., & Bağcıer, F. (2023) · World Neurosurgery · doi:10.1016/j.wneu.2023.11.062 · Cited by 55 · see citing works
Mohapatra, M., Sahu, C., & Mohapatra, S. (2024) · Current Drug Targets · doi:10.2174/0113894501322734241008163304 · Cited by 52 · see citing works
Mithany, R. H., Aslam, S., Abdallah, S., Abdelmaseeh, M. M. A., Gerges, F., Mohamed, M. S., Manasseh, M., Wanees, A., Shahid, M. H., Khalil, M., et al. (2023) · Cureus · doi:10.7759/cureus.47924 · Cited by 51 · see citing works
AI in Indian healthcare: From roadmap to reality
Das, S. K., Dasgupta, R. K., Roy, S. D., & Shil, D. (2024) · Intelligent Pharmacy · doi:10.1016/j.ipha.2024.02.005 · Cited by 48 · see citing works
Yudhistira, B., Adi, P., Mulyani, R., Chang, C., Gavahian, M., & Hsieh, C. (2024) · Comprehensive Reviews in Food Science and Food Safety · doi:10.1111/1541-4337.13413 · Cited by 48 · see citing works
Giebel, G. D., Raszke, P., Nowak, H., Palmowski, L., Adamzik, M., Heinz, P., Tokic, M. C., Timmesfeld, N., Brunkhorst, F., Wasem, J., et al. (2024) · Journal of Medical Internet Research · doi:10.2196/63377 · Cited by 47 · see citing works
Vyas, A., Kumar, K., Sharma, A., Verma, D., Bhatia, D. D., Wahi, N., & Yadav, A. K. (2025) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2025.110178 · Cited by 46 · see citing works
Sarangi, P. K., Narayan, R. K., Mohakud, S., Vats, A., Sahani, D., & Mondal, H. (2023) · Indian journal of radiology and imaging - new series/Indian journal of radiology and imaging/Indian Journal of Radiology & Imaging · doi:10.1055/s-0043-1777746 · Cited by 41 · see citing works
Sallam, M., Al-Mahzoum, K., Alaraji, H., Albayati, N., Alenzei, S., AlFarhan, F., Alkandari, A., Alkhaldi, S., Alhaider, N., Al-Zubaidi, D., et al. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1542769 · Cited by 41 · see citing works
Artificial intelligence (AI) in pharmacy: an overview of innovations
Jarab, A. S., Heshmeh, S. A., & Meslamani, A. Z. A. (2023) · Journal of Medical Economics · doi:10.1080/13696998.2023.2265245 · Cited by 41 · see citing works
Mosleh, R., Jarrar, Q., Jarrar, Y., Tazkarji, M., & Hawash, M. (2023) · Advances in Medical Education and Practice · doi:10.2147/amep.s433255 · Cited by 40 · see citing works
AI in Context: Harnessing Domain Knowledge for Smarter Machine Learning
Miller, T. I., Durlik, I., Łobodzińska, A., Dorobczyński, L., & Jasionowski, R. (2024) · Applied Sciences · doi:10.3390/app142411612 · Cited by 40 · see citing works
Cersosimo, A., Zito, E., Pierucci, N., Matteucci, A., & Fazia, V. M. L. (2025) · Journal of Personalized Medicine · doi:10.3390/jpm15050205 · Cited by 40 · see citing works
Cary, M. P., Gagne, J. C. D., Kauschinger, E. D., & Carter, B. M. (2024) · Creative Nursing · doi:10.1177/10784535241249193 · Cited by 40 · see citing works
Yıldırım, Z., Swanson, K., Wu, X., Zou, J., & Wu, J. C. (2024) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-022724-095035 · Cited by 39 · see citing works
Ethics of artificial intelligence in prenatal and pediatric genomic medicine
Coghlan, S., Gyngell, C., & Vears, D. F. (2023) · Journal of Community Genetics · doi:10.1007/s12687-023-00678-4 · Cited by 38 · see citing works
Lu, H. J., Alhaskawi, A., Dong, Y., Zou, X., Zhou, H., Ezzi, S. H. A., Kota, V. G., Abdulla, M. H. A. H., & Abdalbary, S. A. (2024) · INQUIRY The Journal of Health Care Organization Provision and Financing · doi:10.1177/00469580241266364 · Cited by 38 · see citing works
Zhang, X., Tsang, C. C. S., Ford, D. D., & Wang, J. (2024) · American Journal of Pharmaceutical Education · doi:10.1016/j.ajpe.2024.101309 · Cited by 38 · see citing works
Chatzopoulos, G. S., Koidou, V. P., Tsalikis, L., & Kaklamanos, E. G. (2024) · Journal of Prosthetic Dentistry · doi:10.1016/j.prosdent.2024.10.020 · Cited by 38 · see citing works
Nti, I. K., Adekoya, A. F., Weyori, B. A., & Kyeremeh, F. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100292 · Cited by 38 · see citing works
Abbasi, N., & Hussain, H. K. (2024) · Journal of Artificial Intelligence General science (JAIGS) · doi:10.60087/jaigs.v5i1.207 · Cited by 37 · see citing works
Artificial intelligence in prosthodontics
Hendi, K. D. A., Alyami, M. H., Alkahtany, M., Dwivedi, A. K., & Alsaqour, H. G. (2024) · Bioinformation · doi:10.6026/973206300200238 · Cited by 36 · see citing works
Sallam, M., Al-Mahzoum, K., Alshuaib, O., Alhajri, H., Alotaibi, F., Alkhurainej, D., Al-Balwah, M. Y., Barakat, M. M., & Egger, J. (2024) · BMC Infectious Diseases · doi:10.1186/s12879-024-09725-y · Cited by 36 · see citing works
Petrušić, I., Ha, W., Labastida‐Ramírez, A., Messina, R., Onan, D., Tana, C., & Wang, W. (2024) · The Journal of Headache and Pain · doi:10.1186/s10194-024-01847-7 · Cited by 36 · see citing works
Abadir, P. M., Oh, E. S., Chellappa, R., Choudhry, N. K., Demiris, G., Ganesan, D., Karlawish, J. H., Marlin, B. M., Li, R. M., Dehak, N., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13710 · Cited by 35 · see citing works
Ma, X., Zhang, Q., He, L., Liu, X., Xiao, Y., Hu, J., Cai, S., Cai, H., & Yu, B. (2024) · Frontiers in Oncology · doi:10.3389/fonc.2024.1487676 · Cited by 35 · see citing works
AI-Driven Telerehabilitation: Benefits and Challenges of a Transformative Healthcare Approach
Calabrò, R. S., & Mojdehdehbaher, S. (2025) · Applied Informatics · doi:10.3390/ai6030062 · Cited by 30 · see citing works
Students' perception of the use of artificial intelligence (AI) in pharmacy school
Knobloch, J., Cozart, K., Halford, Z., Hilaire, M. L., Richter, L. M., & Arnoldi, J. D. (2024) · Currents in Pharmacy Teaching and Learning · doi:10.1016/j.cptl.2024.102181 · Cited by 34 · see citing works
Ali, S. M., Razzaque, A., Yousaf, M., & Ali, S. S. (2025) · IEEE Access · doi:10.1109/access.2024.3524884 · Cited by 33 · see citing works
Digitalization in orthopaedics: a narrative review
Youssef, Y., Wet, D. D., Back, D. A., & Scherer, J. N. (2024) · Frontiers in Surgery · doi:10.3389/fsurg.2023.1325423 · Cited by 32 · see citing works
Agrawal, S., & Vagha, S. J. (2024) · Cureus · doi:10.7759/cureus.66225 · Cited by 32 · see citing works
Ending tuberculosis: challenges and opportunities
Gilmour, B., & Alene, K. A. (2024) · Frontiers in Tuberculosis · doi:10.3389/ftubr.2024.1487518 · Cited by 32 · see citing works
The Limitations of Artificial Intelligence in Head and Neck Oncology
Rao, K. N., Fernandez-Alvarez, V., Guntinas-Lichius, O., Sreeram, M. P., de Bree, R., Kowalski, L. P., Forastiere, A., Pace-Asciak, P., Rodrigo, J. P., Saba, N. F., et al. (2025) · Advances in Therapy · doi:10.1007/s12325-025-03198-4 · Cited by 34 · see citing works
Marey, A., Ambrozaite, O., Afifi, A., Agarwal, R., Chellappa, R., Adeleke, S. M., & Umair, M. (2025) · European Radiology · doi:10.1007/s00330-025-12031-z · Cited by 32 · see citing works
Alsanosi, S., & Padmanabhan, S. (2024) · Healthcare · doi:10.3390/healthcare12070788 · Cited by 31 · see citing works
Goel, I., Bhaskar, Y., Kumar, N., Singh, S., Amanullah, M., Dhar, R., & Karmakar, S. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1550407 · Cited by 31 · see citing works
Sallam, M., Al-Mahzoum, K., Almutairi, Y. M., Alaqeel, O., Abu Salami, A., Almutairi, Z. E., Alsarraf, A. N., & Barakat, M. (2024) · International Medical Education · doi:10.3390/ime3040031 · Cited by 30 · see citing works
A critical look into artificial intelligence and healthcare disparities
Li, D. M., Parikh, S., & Costa, A. B. N. (2025) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2025.1545869 · Cited by 30 · see citing works
Biomarkers predicting the efficacy of immune checkpoint inhibitors in hepatocellular carcinoma
Qin, R., Jin, T., & Xu, F. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1326097 · Cited by 29 · see citing works
Role of artificial intelligence in behavior management of pediatric dental patients—a mini review
Acharya, S., Godhi, B. S., Saxena, V., Assiry, A. A., Alessa, N. A., Dawasaz, A. A., Alqarni, A., & Karobari, M. I. (2024) · Journal of Clinical Pediatric Dentistry · doi:10.22514/jocpd.2024.055 · Cited by 29 · see citing works
Artificial intelligence-driven transformations in diabetes care: a comprehensive literature review
Iftikhar, M., Saqib, M., Qayyum, S. N., Asmat, R., Mumtaz, H., Rehan, M., Ullah, I., Uddin, I., Noori, S., Khan, M., et al. (2024) · Annals of Medicine and Surgery · doi:10.1097/ms9.0000000000002369 · Cited by 29 · see citing works
Belbase, P., Bhusal, R., Ghimire, S. S., Sharma, S., & Banskota, B. (2024) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2024.1442254 · Cited by 28 · see citing works
Smoła, P., Młoźniak, I., Wojcieszko, M., Zwierczyk, U., Kobryn, M., Rzepecka, E., & Duplaga, M. (2025) · Frontiers in Digital Health · doi:10.3389/fdgth.2025.1458685 · Cited by 28 · see citing works
Large Language Models in Oncology: Revolution or Cause for Concern?
Caglayan, A., Slusarczyk, W., Rabbani, R. D., Ghose, A., Papadopoulos, V. P., & Boussios, S. (2024) · Current Oncology · doi:10.3390/curroncol31040137 · Cited by 27 · see citing works
ChatGPT Performance in Diagnostic Clinical Microbiology Laboratory-Oriented Case Scenarios
Sallam, M., Al‐Salahat, K., & Al-Ajlouni, E. (2023) · Cureus · doi:10.7759/cureus.50629 · Cited by 26 · see citing works
Reshaping the healthcare world by AI-integrated wearable sensors following COVID-19
Khan, B., Khalid, R. T., Wara, K. U., Masrur, M. A., Khan, S., Khan, W. U., Amara, U., & Abdullah, S. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.159478 · Cited by 26 · see citing works
Self-citationErden, Y., Temel, M. H., & Bağcıer, F. (2024) · Archives of Osteoporosis · doi:10.1007/s11657-024-01376-5 · Cited by 26 · see citing works
Raza, S., Shaban-Nejad, A., Dolatabadi, E., & Mamiya, H. (2024) · IEEE Access · doi:10.1109/access.2024.3509353 · Cited by 25 · see citing works
Almoammar, K. A. (2024) · Children · doi:10.3390/children11020140 · Cited by 25 · see citing works
Wójcik, Z., Dimitrova, V. G., Warrington, L., Velikova, G., & Absolom, K. L. (2025) · Health and Quality of Life Outcomes · doi:10.1186/s12955-025-02365-z · Cited by 25 · see citing works
Use of artificial intelligence in medical education: A strength or an infirmity
Sarfaraz, S., Khurshid, Z., & Zafar, M. S. (2023) · Journal of Taibah University Medical Sciences · doi:10.1016/j.jtumed.2023.06.008 · Cited by 25 · see citing works
A Justifiable Investment in AI for Healthcare: Aligning Ambition with Reality
Karpathakis, K., Morley, J., & Floridi, L. (2024) · Minds and Machines · doi:10.1007/s11023-024-09692-y · Cited by 24 · see citing works
Khan, B., Khalid, R. T., Masrur, M. A., Awais, M., Khan, B., & Khoo, B. L. (2025) · Chemical Engineering Journal · doi:10.1016/j.cej.2025.170117 · Cited by 24 · see citing works
Self-citationArtificial Intelligence for Noninvasive Health Diagnostics
Wankhede, P., Bhuyar, D. L., Zanwar, S. R., Pawar, R., Jadhav, M. R., Gandhewar, N., Kulkarni, M. B., Bhaiyya, M. L., & Haick, H. (2025) · ACS Sensors · doi:10.1021/acssensors.5c03171 · Cited by 25 · see citing works
Patil, D. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5057432 · Cited by 24 · see citing works
Şahin, M. F., Keleş, A., Özcan, R., Doğan, Ç., Topkaç, E. C., Akgül, M., & Yazıcı, C. M. (2024) · Sexual Medicine · doi:10.1093/sexmed/qfae036 · Cited by 23 · see citing works
Review on Emerging Frontiers in Medical Sensing: Innovations Shaping the Future of Healthcare
Kirubakaran, D. (2025) · Biomedical Materials & Devices · doi:10.1007/s44174-025-00385-3 · Cited by 23 · see citing works
Godoy, C. A., Miele, F., Mäkitie, L., Fiorenzato, E., Koivu, M., Bakker, L. J., Groot, C. A. U., Redekop, K., & van Deen, W. K. (2024) · Patient · doi:10.1007/s40271-023-00669-0 · Cited by 23 · see citing works
Large Language Models in peri-implant disease: How well do they perform?
Koidou, V. P., Chatzopoulos, G. S., Tsalikis, L., & Kaklamanos, E. G. (2025) · Journal of Prosthetic Dentistry · doi:10.1016/j.prosdent.2025.02.008 · Cited by 22 · see citing works
Early Detection of Lung Cancer: A Review of Innovative Milestones and Techniques
Habbab, F. M., Bédard, E. L. R., Joy, A. A., Alam, Z., Abraham, A., & Roa, W. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14217812 · Cited by 22 · see citing works
AI-driven business analytics for SMES: Unlocking value through predictive and prescriptive analytic
Ocran, G., Yusuf, S. O., Owusu, P., Boateng, E. A., Krampah, S. O., & Paul-Adeleye, A. H. (2024) · International Journal of Science and Research Archive · doi:10.30574/ijsra.2024.13.1.2001 · Cited by 21 · see citing works
Khalaf, A. D., Hamdan, H., Halin, A. B. A., & Manshor, N. B. (2025) · IEEE Access · doi:10.1109/access.2025.3569170 · Cited by 21 · see citing works
Alves, E., Gurupadayya, B., & Prabhakaran, P. (2025) · Critical Reviews in Analytical Chemistry · doi:10.1080/10408347.2025.2575352 · Cited by 21 · see citing works
- Authors
- khan, B., Fatima, H., Qureshi, A., Kumar, S., Hanan, A., Hussain, J., & Abdullah, S.
- Affiliations
- Riphah International University (PK)
- Mehran University of Engineering and Technology (PK)
- NED University of Engineering and Technology (PK)
- Corresponding author
- khan, Bangul
- Venue
- Biomedical Materials & Devices
- Published
- 2023-02-08
- Volume
- 1
- Issue
- 2
- Pages
- 731-738
- ISSN
- 2731-4812 (ISSN-L)
- 2731-4820
- PMC
- PMC9908503
- OpenAlex
- W4319454440
- Cited by
- 461
- References
- 51
- Citations by year
- 2026: 64 · 2025: 166 · 2024: 185 · 2023: 46
- FWCI
- 5.42
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Biomedical Materials & Devices (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- University of Engineering and Technology, Lahore
- Mälardalens högskola
- Mehran University of Engineering and Technology
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Keywords
- artificial intelligence in healthcare, data security, privacy, health records, data breaches, ethical use of AI, machine learning ethics, medical records confidentiality
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