Artificial Intelligence Applications in Predictive Healthcare Systems

Predictive systems made possible by artificial intelligence (AI) are revolutionising healthcare by allowing for more precise, rapid, and individualised medical procedures. Using data analytics, NLP, and machine learning algorithms, this article delves into the ways AI is being applied to predictive healthcare, specifically in the areas of illness risk prediction, treatment plan optimisation, and patient outcome improvement. Using massive datasets derived from genetic information, electronic health records, and real-time monitoring equipment, predictive algorithms seek out trends and outliers that can suggest possible health problems. In the long run, these innovations help save healthcare costs and improve service delivery by facilitating early diagnosis, preventative care, and effective use of resources. Data privacy, ethics, and the necessity for legal frameworks are some of the obstacles to AI implementation that the research delves into. Intelligent, person-centred medical treatment is possible with the help of AI-driven prediction technologies, which will allow the healthcare industry to change its focus from a reactive to a proactive paradigm.

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Publication Details

Journal
Journal of Advances and Scholarly Researches in Allied Education
Published
2025-01-01
DOI
https://doi.org/10.29070/s2zg4656
Primary Topic
Artificial Intelligence in Healthcare
Type
article
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article

Artificial Intelligence Applications in Predictive Healthcare Systems

Sudip Sikdar, Kalyani S. Sugarwar
Journal of Advances and Scholarly Researches in Allied Education
Artificial Intelligence in Healthcare
article

Artificial Intelligence Applications in Predictive Healthcare Systems

Sudip Sikdar, Kalyani S. Sugarwar
article en

Abstract

Predictive systems made possible by artificial intelligence (AI) are revolutionising healthcare by allowing for more precise, rapid, and individualised medical procedures. Using data analytics, NLP, and machine learning algorithms, this article delves into the ways AI is being applied to predictive healthcare, specifically in the areas of illness risk prediction, treatment plan optimisation, and patient outcome improvement. Using massive datasets derived from genetic information, electronic health records, and real-time monitoring equipment, predictive algorithms seek out trends and outliers that can suggest possible health problems. In the long run, these innovations help save healthcare costs and improve service delivery by facilitating early diagnosis, preventative care, and effective use of resources. Data privacy, ethics, and the necessity for legal frameworks are some of the obstacles to AI implementation that the research delves into. Intelligent, person-centred medical treatment is possible with the help of AI-driven prediction technologies, which will allow the healthcare industry to change its focus from a reactive to a proactive paradigm.

Journal of Advances and Scholarly Researches in Allied EducationVol. 22(01)
Shivaji University (IN), Dr Panjabrao Deshmukh Krishi Vidyapeeth (IN)
Openalex Percentile: Top 92%
Artificial Intelligence in Healthcare
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Artificial Intelligence Applications in Predictive Healthcare Systems — Sudip Sikdar, Kalyani S. Sugarwar · Journal of Advances and Scholarly Researches in Allied Education (2025) | TGRS Research Map | TGRS