Authors - Prachita Chaudhari, Shubham Kishor Kadam, Shiwani wagh, Pankajkumar Anawade, Deepak Sharma, Chhitij Raj Abstract - One of such industries is healthcare, where data-driven methods attract much attention, and one among them is the field of predictive analytics that is already making a great difference in the healthcare industry concerning its capacity to enhance early diagnosis and treatment. Through this, whole care is provided, and this implies that the problem of fragmented care addresses systemic issues such as inefficiencies and inflation of costs. Predictive analytics is the most effective in the prediction of risks of disease, i.e. making care a thing related to the individual patient. Besides, it can be utilized to monitor populations and enhance the management of population health utilizing its combination of machine learning, natural language processing and deep learning. Solutions that offer the following benefits, including reduced misdiagnosis, re-source utilization, and affordable access to health care, are also being created with the help of the main enabling technologies including AI, IoT, and big data. Nevertheless, issues like the quality of the data, technical issues, ethical concerns and compliance with laws persist. Future work still to be done areas can be seen in the application of new technologies like quantum computing to answer questions about the public health, real time data that uses IoT, and the application of other mediating technologies in underserved locations that can instill equity and sustainability. Being fueled by the collaboration of various professionals, e.g., clinicians, data scientists, and policy-makers, predictive analytics is bound to enhance patient outcomes and catalyze the better provision of preventive, personalized, and responsibility healthcare solutions.
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