AI-DRIVEN REAL-TIME MONITORING AND PREDICTION OF POST-SURGICAL COMPLICATIONS USING WEARABLE TECHNOLOGY
Mallayev Oybek Usmankulovich, Qodirov Rahimjon Rasuljon o‘g‘li
Keywords:
Artificial Intelligence, Wearable Technology, Post-surgical Complications, Real-Time Monitoring, Predictive Analytics.Abstract
Post-surgical complications are a significant concern in healthcare, leading to increased morbidity, mortality, and healthcare costs. Traditional methods of monitoring rely on periodic assessments, which can miss critical signs of complications in their early stages. This article explores the potential of AI-driven real-time monitoring and prediction of post-surgical complications using wearable technology. We discuss how wearable sensors can continuously collect physiological data, which is then analyzed by artificial intelligence algorithms to identify patterns and predict potential complications. This approach has the potential to revolutionize post-surgical care by enabling early intervention and improved patient outcomes.
References
Alipour Z, Rahimi F, Asadi F, et al. "Real-Time Detection of Postoperative Complications Using Wearable Devices: A Systematic Review." Telemedicine and e-Health. 2020; 26(8): 977-986.
Wong DJN, Yeung JH, Mehta N, et al. "Impact of Wearable Continuous Monitoring on Clinical Outcomes in Surgical and Medical Patients: Systematic Review and Meta-Analysis." Journal of Medical Internet Research. 2020; 22(7): e18636.
Jiang F, Jiang Y, Zhi H, et al. "Artificial Intelligence in Healthcare: Past, Present, and Future." Stroke and Vascular Neurology. 2017; 2(4): 230-243.
Rajkomar A, Dean J, Kohane I. "Machine Learning in Medicine." New England Journal of Medicine. 2019; 380(14): 1347-1358.
Nguyen DP, Ganta A, Lugo JM, et al. "A Review of Wearable Technology in Medicine: Current Challenges and Future Prospects." IEEE Reviews in Biomedical Engineering. 2020; 13: 178-188.
Gulshan V, Peng L, Coram M, et al. "Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs." JAMA. 2016; 316(22): 2402-2410.
Davenport T, Kalakota R. "The Potential for Artificial Intelligence in Healthcare." Future Healthcare Journal. 2019; 6(2): 94-98.
Hüske-Kraus D, Kraus J, Rosenfeld M. "Wearable Technology in Hospital Care: Possibilities and Pitfalls." International Journal of Environmental Research and Public Health. 2020; 17(3): 877.
Chui M, Manyika J, Miremadi M. "Where Machines Could Replace Humans—and Where They Can’t (Yet)." McKinsey Quarterly. 2016.
Ho D, Voelker J, Surapaneni P, et al. "Real-Time Monitoring and Prediction of Decompensation in Patients With Chronic Heart Failure Using Wearable Technology." American Journal of Cardiology. 2020; 125(4): 624-629.
