Enhancing Healthcare with Intelligent Solutions
Abstract
This paper explores the enhancement of healthcare through intelligent solutions enabled by AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing various aspects of healthcare delivery, including diagnosis, treatment, and patient care. The study highlights the application of AI techniques such as medical image analysis, predictive modeling, and natural language processing in improving accuracy, efficiency, and patient outcomes in healthcare settings. Additionally, it discusses the integration of AI with electronic health records, wearable devices, and telemedicine platforms to enable personalized medicine, remote monitoring, and healthcare accessibility. The paper also addresses challenges such as data privacy, regulatory compliance, and ethical concerns in the adoption of AI-driven engineering solutions in healthcare. It emphasizes the importance of interdisciplinary collaboration, clinical validation, and patient-centered innovation in harnessing AI's potential to transform healthcare delivery and improve population health outcomes.
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- 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., ... & Kim, R. (2016). Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA, 316(22), 2402-2410.
- Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., ... & Wang, Y. (2017). Artificial intelligence in healthcare: Past, present and future. Stroke and Vascular Neurology, 2(4), 230-243.
- Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T. (2018). Deep learning for healthcare: Review, opportunities and challenges. Briefings in Bioinformatics, 19(6), 1236-1246.
- Obermeyer, Z., & Emanuel, E. J. (2016). Predicting the future—Big data, machine learning, and clinical medicine. New England Journal of Medicine, 375(13), 1216-1219.
- Rajkomar, A., Dean, J., Kohane, I., & Butte, A. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347-1358.
- Topol, E. J. (2019). High-performance medicine: The convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56.