The Transformative Role of Artificial Intelligence in Healthcare
Keywords:
Artificial Intelligence, Healthcare Innovation, Medical Diagnostics, Clinical Decision Support, Health Data Analytics, Ethical AIAbstract
Artificial Intelligence (AI) has emerged as one of the most transformating technologies in the healthcare sector, greatly enhancing diagnostics, patient care, drug discovery, and administrative efficiency. This research paper examines the influence of AI in healthcare by utilizing secondary data sourced from global reports, peer-reviewed journals, and industry publications. The study evaluates key AI applications, advantages, challenges, and future outlooks, accompanied by a comprehensive Review of Literature (ROL). The findings indicate that AI improves diagnostic precision, lowers healthcare expenses, streamlines clinical workflows, and speeds up medical research. Nevertheless, challenges such as data privacy concerns, algorithmic bias, and a shortage of skilled professionals continue to hinder widespread implementation. The paper concludes with suggestions for the responsible and effective integration of AI in the healthcare field.
References
Davenport, T., & Kalakota, R. (2019). The possibilities of artificial intelligence in the field of healthcare. Future Healthcare Journal, 6(2), 94–98.
Esteva, A., Kuprel, B., Novoa, R., et al. (2017). Classification of skin cancer at a dermatologist level using deep neural networks. Nature, 542(7639), 115–118.
Hughes, J. P., Rees, S., Kalindjian, S. B., & Philpott, K. L. (2021). Foundations of early drug discovery facilitated by artificial intelligence. Nature Reviews Drug Discovery, 20, 199–216.
Rajkomar, A., Dean, J., & Kohane, I. (2019). The application of machine learning in the medical field. New England Journal of Medicine, 380(14), 1347–1358.
Sharma, A., Kaur, P., & Singh, D. (2022). The significance of AI-enabled telemedicine during and following the COVID-19 pandemic. Journal of Medical Systems, 46(8).
Shickel, B., Tighe, P., Bihorac, A., & Rashidi, P. (2018). Deep EHR: Clinical decision support powered by AI. IEEE Journal of Biomedical and Health Informatics, 22(5), 1589–1604.
Topol, E. (2019). Medicine of high performance: The merging of human and artificial intelligence. Nature Medicine, 25(1), 44–56.
P. Devi, H. Kaur, R. Kumar, S. Aluvala and S. Singh, "Artificial Intelligence is Revolution or Devolution for Employability," 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Bengaluru, India, 2023, pp. 367-371, doi: 10.1109/ICIMIA60377.2023.10425850.
Shaikh, S. A., & Jagirdar, A. H. (2026). Beyond AI dependence: Pedagogical approaches to strengthen student reasoning and analytical skills. In S. Khan & P. Pringuet (Eds.), Empowering learners with AI: Strategies, ethics, and frameworks (Chapter 8, pp. 1–16). IGI Global. https://doi.org/10.4018/979-8-3373-7386-7.ch008
Shaikh, S. A. (2024). Empowering Gen Z and Gen Alpha: A comprehensive approach to cultivating future leaders. In Futuristic Trends in Management (IIP Series, Vol. 3, Book 9, Part 2, Chapter 2). IIP Series. https://doi.org/10.58532/V3BHMA9P2CH2
Chougle, Z. S., & Shaikh, S. (2022). To understand the impact of Ayurvedic health-care business & its importance during COVID-19 with special reference to “Patanjali Products”. In Proceedings of the National Conference on Sustainability of Business during COVID-19, IJCRT, 10(1),
Bhagat, P. H., & Shaikh, S. A. (2025). Managing health care in the digital world: A comparative analysis on customers using health care services in Mumbai suburbs and Pune city. IJCRT. Registration ID: IJCRT_216557.
Parikh, V. C. (2022) Strategic talent management in education sector around organizational life cycle stages! JOURNAL OF THE ASIATIC SOCIETY OF MUMBAI, SSN: 0972-0766, Vol. XCV, No.11.
Parikh, V. (2023). Whistleblowing in B-Schools, Education and Society, Vol-47, Issue – 1, Pg. 183-189
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
