AI for Remote Patient Monitoring: Improving Chronic Disease Management and Preventive Care
Abstract
Remote patient monitoring (RPM) has emerged as a key strategy in managing chronic diseases such as hypertension, diabetes, and heart disease. This paper explores the role of AI and machine learning in enhancing RPM systems by analyzing data from wearable devices, sensors, and mobile applications. We discuss how AI algorithms can detect early signs of disease exacerbation, predict potential complications, and provide real-time feedback to both patients and healthcare providers. Additionally, the paper examines the challenges of integrating AI into existing healthcare infrastructure, ensuring data security, and achieving patient compliance for long-term disease management.
References
KOLLURI, V. (2016). MACHINE LEARNING IN MANAGING HEALTHCARE SUPPLY CHAINS: HOW MACHINE LEARNING.
KOLLURI, V. (2014). VULNERABILITIES: EXPLORING RISKS IN AI MODELS AND ALGORITHMS.
Kolluri, V. (2016). A PIONEERING APPROACH TO FORENSIC INSIGHTS: UTILIZATION AI FOR CYBERSECURITY INCIDENT INVESTIGATIONS. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), E-ISSN, 2348-1269.
Kolluri, V. (2016). A PIONEERING APPROACH TO FORENSIC INSIGHTS: UTILIZATION AI FOR CYBERSECURITY INCIDENT INVESTIGATIONS. IJRAR-International Journal of Research and Analytical Reviews (IJRAR), E-ISSN, 2348-1269.
Gatla, T. R. (2017). A SYSTEMATIC REVIEW OF PRESERVING PRIVACY IN FEDERATED LEARNING: A REFLECTIVE REPORT-A COMPREHENSIVE ANALYSIS. IEJRD-International Multidisciplinary Journal, 2(6), 8.
Gatla, T. R. (2019). A CUTTING-EDGE RESEARCH ON AI COMBATING CLIMATE CHANGE: INNOVATIONS AND ITS IMPACTS. INNOVATIONS, 6(09).
Gatla, T. R. “A GROUNDBREAKING RESEARCH IN BREAKING LANGUAGE BARRIERS: NLP AND LINGUISTICS DEVELOPMENT. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882.
Gatla, T. R. (2018). AN EXPLORATIVE STUDY INTO QUANTUM MACHINE LEARNING: ANALYZING THE POWER OF ALGORITHMS IN QUANTUM COMPUTING. International Journal of Emerging Technologies and Innovative Research (www. jetir. org), ISSN, 2349-5162.
Pindi, V. (2018). AI for Surgical Training: Enhancing Skills through Simulation. International Numeric Journal of Machine Learning and Robots, 2(2).
Pindi, V. (2017). AI in Rehabilitation: Redefining Post-Injury Recovery. International Numeric Journal of Machine Learning and Robots, 1(1).
Velaga, S. P. (2014). DESIGNING SCALABLE AND MAINTAINABLE APPLICATION PROGRAMS. IEJRD-International Multidisciplinary Journal, 1(2), 10.
Velaga, S. P. (2016). LOW-CODE AND NO-CODE PLATFORMS: DEMOCRATIZING APPLICATION DEVELOPMENT AND EMPOWERING NON-TECHNICAL USERS. IEJRD-International Multidisciplinary Journal, 2(4), 10.
Velaga, S. P. (2017). “ROBOTIC PROCESS AUTOMATION (RPA) IN IT: AUTOMATING REPETITIVE TASKS AND IMPROVING EFFICIENCY. IEJRD-International Multidisciplinary Journal, 2(6), 9.
Velaga, S. P. (2018). AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS. International Journal of Innovations in Engineering Research and Technology, 5(2), 78-85.
Velaga, S. P. (2020). AIASSISTED CODE GENERATION AND OPTIMIZATION: LEVERAGING MACHINE LEARNING TO ENHANCE SOFTWARE DEVELOPMENT PROCESSES. International Journal of Innovations in Engineering Research and Technology, 7(09), 177-186.
Velaga, S. P. R. (2021). AI in Health Monitoring: Continuous Care through Wearable Technology. International Journal of Holistic Management Perspectives, 2(2).
Velaga, S. P. R. (2020). AI in Cardiovascular Care: From Early Detection to Personalized Treatment. International Journal of Holistic Management Perspectives, 1(1).
Velaga, S. P. R. (2018). AI in Healthcare Chatbots: Enhancing Patient Engagement and Support. International Numeric Journal of Machine Learning and Robots, 2(2).
Velaga, S. P. R. (2017). AI in Healthcare Accessibility: Bridging the Urban-Rural Divide. International Numeric Journal of Machine Learning and Robots, 1(1).
Veera All 7(8)
Pindi, V. (2018). NATURAL LANGUAGE PROCESSING(NLP) APPLICATIONS IN HEALTHCARE: EXTRACTING VALUABLE INSIGHTS FROM UNSTRUCTURED MEDICAL DATA. International Journal of Innovations in Engineering Research and Technology, 5(3), 1-10.
Pindi, V. (2019). A AI-ASSISTED CLINICAL DECISION SUPPORT SYSTEMS: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT RECOMMENDATIONS. International Journal of Innovations in Engineering Research and Technology, 6(10), 1-10.