An Interactive Healthcare Recommendation System Using Big Data Analytics

Digital innovation and technological disruption are advancing the healthcare sector at an extremely fast rate. The enormous volume of medical services information keeps on mounting consistently, making it harder and truly challenging to track down any type of helpful data. However, in order to mine the data and obtain business intelligence, a comprehensive big data approach is necessary. The ability to identify serious diseases very quickly and provide better medical care to the correct patient at the right time to improve quality of life are only two of the many advantages of big data analytics for the healthcare industry. This paper presents An Interactive Healthcare recommendation System using Big Data Analytics. This system analyzes the results of routine physical examinations to identify health risks and provide users with personalized healthcare services, such as recommendations for exercise and diets. They developed several interactive methods, so users could immediately provide the system with feedback on their vital signs and receive recommendations for improving their health. The prediction model loses accuracy as more MAE is collected. Another observation is that performance improves when a larger number of parties collaborate.