The Role of Artificial Intelligence and Machine Learning in Transforming Healthcare
EOI: 10.11242/viva-tech.01.05.001
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Citation
Prof. Krutika Vartak,Abdullah Jatu , Moinuddin Khan,"The Role of Artificial Intelligence and Machine Learning in Transforming Healthcar", VIVA-IJRI Volume 1, Issue 7, Article 1, pp. 1-14, 2023. Published by Master of Computer Application Department, VIVA Institute of Technology, Virar, India.
Abstract
The role of Artificial Intelligence (AI) and Machine Learning (ML) in transforming healthcare is profound and multidimensional, heralding a new era of medical innovation and improved patient care. AI and ML technologies are revolutionizing healthcare by enhancing diagnostic accuracy, optimizing treatment plans, personalizing patient care, and improving healthcare delivery systems. These technologies analyse vast amounts of healthcare data, including electronic health records, medical imaging, and genomics, to uncover patterns and insights that were previously inaccessible. AI algorithms support clinicians in making more informed decisions, predicting disease outbreaks, and identifying potential therapeutic interventions. ML models facilitate early disease detection, monitor patient health in real-time, and predict patient outcomes, thereby enabling preventive healthcare measures. Additionally, AI and ML are instrumental in drug discovery and development, significantly reducing the time and costs associated with bringing new treatments to market. The integration of AI and ML into healthcare holds the promise of enhancing patient outcomes, reducing healthcare costs, and addressing the challenges posed by an ever-growing and aging global population. However, this integration also raises ethical, privacy, and security concerns that must be carefully managed. Overall, the role of AI and ML in healthcare is transformative, offering unprecedented opportunities to improve health and well-being on a global scale.
Keywords
AI (Artificial Intelligence),Data analysis, Diagnostic accuracy, Drug discovery, Early disease detection, Ethical considerations, Healthcare transformation (Machine Learning),Personalized care, Predictive analytics, Preventive healthcare,Privacy,Security,Treatment optimization.
References
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