International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Transforming Patient Care: The Role of Predictive Analytics in Medical Diagnosis and Resource Allocation

Author(s) Prof. Ms. Medha Vaibhav Joshi, Vaishali Raghuvir Hire, Poonam Sharad Kachave, Rajendra Vasantrao Patil
Country India
Abstract In the field of the health care sector models for prediction is a significant and rapidly developing subject that makes use of information, statistics, and artificially intelligent algorithms to forecast future health outcomes, expedite medical procedures, and enhance patient care. In recent years, it has garnered a substantial amount of attention as a result of developments in technological advances, the accessibility of enormous amounts of information pertaining to medical care and an increasing realization of its potential to revolutionize the providing of healthcare. This multifaceted strategy mixes clinical expertise, statistical analysis, and computer programs for prediction to allow medical professionals to come to decisions that are more up-to-date distribute resources in an effective way, and eventually boost the treatment of patients while also saving expenses. The usefulness of forecasting machine learning techniques for healthcare diagnosis and resource utilization is discussed in this body of work. This study not only emphasizes the crucial role of predictive models in the healthcare industry, but it also investigates the difficulties associated with utilizing predictive models in healthcare and discusses potential future approaches.
Keywords Machine Learning, AI, Predictive Models, Data imbalance, Big data
Field Engineering
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-03-20
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.39491
Short DOI https://doi.org/g89vtk
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