Machine Learning-Based Predictive Modelling For Healthcare

Abstract

machine learning and deep learning approaches can be used to efficiently analyse this data and produce insightful findings.   By adding data from social media, genetics, medical records, environmental data, and other sources to healthcare data, a comprehensive understanding of various data streams can also be attained.   Additionally, the suggested framework analyzing health trends in relation to the symptoms experienced by certain populations and individual treatment decisions.  This method can be used to calculate the proportion of the population that sought medical attention within a given time frame.   In recent decades, the 'ecology of medical care' theory has gained widespread acceptance in academic circles. Because the system is dynamic and scalable, medical practitioners often face new difficulties, changing duties, and continuous disruptions.  Because of this heterogeneity, healthcare providers frequently make identifying diseases a secondary concern. In addition to highlighting the inherent challenges of implementing machine learning and deep learning techniques in the healthcare sector, this paper attempts to provide a thorough overview of the methods currently employed in healthcare prediction.