The Impact of AI on Reducing Diagnostic Errors in Pathology
Abstract
This study examines the effectiveness of AI in reducing diagnostic errors within pathology. Utilizing deep learning algorithms to analyze histopathological images, our findings reveal a marked reduction in misdiagnoses compared to traditional methods. This research underscores the potential of AI to enhance accuracy and reliability in pathology, ultimately improving patient outcomes.
References
Patel, N., & Singh, V. (2021). Exploring AI and ML in public health: Challenges and opportunities. Public Health Reports, 138(4), 454-460. https://doi.org/10.1177/00333587221090076
Roberts, E., & Garcia, M. (2021). AI in healthcare: Bridging gaps in patient care. Journal of Health Economics, 45, 55-66. https://doi.org/10.1016/j.jhealeco.2023.10.002
Kondru, V. L. P. (2015). Comparative Analysis of Healthcare Systems: A Study of India and the United States. Transactions on Latest Trends in Health Sector, 7(7).
Kondru, V. L. P. (2015). Electronic Health Care Records-Boon To Industry. International Journal of Medical Informatics and AI, 2(2), 1-18.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Kondru, V. L. P. (2014). Comparative Analysis of Oral Cancer Prevalence: Rural vs. Urban India and India vs. Developed . Journal of Healthcare Data Science and AI , 1(1), 1-20.
Kondru, V. L. P. (2014). Understanding Fluorosis: Implications for Dental and General Health. Transactions on Latest Trends in Health Sector, 6(6).
Zhao, X., & Li, F. (2021). Machine learning in healthcare: Trends and future directions. Artificial Intelligence in Medicine, 127, 102-115. https://doi.org/10.1016/j.artmed.2023.102115
