Big data analytics and machine learning: Personalized, predictive health and boost exactitude medicine research

Healthcare data is enabling physician in building predictive models and better patient profiles for more effective anticipation, diagnosis and treatment of various diseases. In addition, partnerships and collaborations between healthcare communities and researchers have resulted into the development of data pools, which can be used for establishing better personalized healthcare models. The increased use of artificial intelligence and machine learning is shifting the paradigm of medical research and treatment. These advanced technologies are providing researchers or medical practitioner real-time access to every white paper and clinical case study conducted on a genetic disorder and also help in detecting fraud in healthcare quickly and efficiently, with the use of statistical tools and algorithms that can help a faster development of more accurately targeted vaccines with a cost effective ways for discovering more clinically relevant ways to analyses the disease and treat the patients in an effective manner. The objective of proposed approach to develop such mechanism to read patients clinical records, radiology data and provide the insight on the disease and allows researchers or medical practitioner to not only understand the full scope of a medical condition, but further shorten the amount of time it takes to develop a cure, treatment options, helping, and healing patients in need of healthcare.