Advancing Patient-Centered Care through AI-Driven Medical Informatics and Real-Time Health Data Analysis
DOI:
https://doi.org/10.56294/mw2024506Keywords:
Artificial Intelligence, Patient-Centered Care, Medical Informatics, Real-Time Health Data, Predictive AnalyticsAbstract
In the quickly evolving sector of healthcare, the marriage of artificial intelligence (AI) with medical technology has drastically revolutionised the way patient-centered care is given. By real-time health data analysis, AI-driven solutions enable healthcare professionals to provide more individualised, effective, proactive treatment. By means of its applications in real-time health data analysis and medical computing, this study explores how artificial intelligence might support patient-centered care enhancement. Big volumes of patient data including information from smart devices, clinical records, and medical images are handled by artificial intelligence algorithms including predictive analytics, natural language processing, and machine learning models. Along with helping clinicians make better judgements, these instruments increase patient involvement, happiness, and likelihood of excellent outcomes. The key advantage of artificial intelligence-driven medical informatics is that it can provide real-time patient health information to healthcare professionals so they may respond fast on new medical problems or probable hazards. Predictive models, for instance, may recommend certain treatment regimens, forecast the course of an illness, and identify potential issues before they become very major. Particularly for those who live in remote or poor regions, AI may also enable telemedicine and online monitoring systems, therefore helping to make healthcare more accessible. Moving the emphasis from reactive care to focused, preventive care helps AI-driven solutions empower individuals to take control of their own health. Better healthcare outcomes follow from simpler patient and healthcare worker collaboration made possible by combined use of artificial intelligence and medical computers. Using these technologies does, however, also present challenges like concerns about data security, the need for consistent procedures, and ensuring ethical usage of artificial intelligence in medical environments.
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Copyright (c) 2024 Swati Kemothi, Sujayaraj Samuel Jayakumar, Swarna Swetha Kolaventi, Pratyashi Satapathy, Kollathur Sudheer, Gunveen Ahluwalia, Ansh Kataria (Author)
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