Artificial Intelligence in Healthcare: Enhancing Diagnostics and Treatment
Abstract
Artificial Intelligence (AI) is revolutionizing healthcare by improving diagnostics, treatment recommendations, and patient care. This paper explores the significance of AI in healthcare, emphasizing its role in medical imaging analysis, predictive analytics, and personalized medicine. It delves into various aspects, including machine learning algorithms, electronic health records (EHRs), and telemedicine applications. The discussion includes the benefits of AI in healthcare, such as early disease detection, reduced medical errors, and improved patient outcomes. Moreover, the paper addresses the challenges and considerations in adopting AI solutions, including data privacy and regulatory compliance. Through a review of AI applications in healthcare, the study highlights the positive outcomes associated with the integration of AI in the medical field.
Share and Cite
Article Metrics
References
- Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118.
- Gulshan, V., Peng, L., Coram, M., Stumpe, M. C., Wu, D., Narayanaswamy, A., ... & Webster, D. R. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 316(22), 2402-2410.
- Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56.
- Zheng, J., Gou, L., Zhang, Z., & Tang, Y. (2019). Internet hospital: Cross-sectional survey. Journal of Medical Internet Research, 21(4), e12860.
- Zhou, L., Wang, L., & Palakal, M. (2012). Implementation of electronic medication administration record system at an open-door health care service. Journal of Medical Systems, 36(6), 3857-3867.