In the editorial "Medical science, technology and Digital Health – Need for holistic integration," published in the Indian Journal of Anaesthesia in October 2023, Dr. Rakesh Garg discusses the increasing integration of artificial intelligence (AI) and machine learning (ML) in medical practice and its potential implications for patient outcomes.
AI and ML have found their way into various clinical domains due to their ability to learn, reason, interpret data, and make decisions. The use of AI and ML depends on mathematical models and complex algorithms, and this reliance on available information and data interpretation remains a limitation with a potential for bias. To make AI more effective, it should consider genetic and demographic variations and move towards personalized medicine, necessitating the collection of extensive, detailed data. The integration of electronic health records and anaesthesia information management systems with ML algorithms can enable real-time patient management and outcome predictions. Dr. Garg emphasizes the importance of integrating AI and ML into simulation-based learning in anesthesiology to enhance simulator-human interaction and provide more personalized training. Collaboration between engineering and medical science experts is crucial for the development of predictive models and the appropriate use of these technologies in healthcare.
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