Advancement in Healthcare Data Analysis: Unveiling the Power of Machine Learning for Predictive Modeling and Future Challenges

Abstract

Healthcare analysis of data is growing as one of the most interesting research areas in recent decades. Sensor data is collected by a variety of wearable and smart devices. Processing this initial data manually is really difficult. The use of machine learning has evolved into an important data processing technique. To more precisely predict the results of healthcare data, artificial intelligence (AI) employs a number of statistical approaches as well as intricate algorithms. The application of ML algorithms for examining different kinds of healthcare information is then discussed in this study. The purpose of this work is to help researchers gain a complete understanding of automatic learning as well as its utilization in healthcare facilities. We proposed a classification of machine learning-based systems in healthcare in this research. We expect that this review paper will help experts become acquainted with the most recent research on ML applications in medicine, identify obstacles in this field, and focus on deep learning approaches in the future because they are extremely powerful tools for addressing healthcare concerns.