Abstract
Machine learning advancements have spurred a revolution in healthcare by making it possible to create prediction models for early disease diagnosis. This report introduces the Multiple Disease Prediction System (MDPS), a state-of-the-art approach that uses machine learning to forecast the likelihood of several diseases based on patient data, including medical history, lifestyle, and demographics. The MDPS addresses the growing difficulties in healthcare by focusing on the early detection of multiple diseases. Some of its crucial components include data preparation, feature selection, model training and disease Detection. Despite advantages like early detection and cost savings, dealing with data privacy, model interpretability, and continuous improvements is essential for MDPS's ethical and efficient usage in healthcare. As a result, MDPS has a significant potential to enhance public health and minimize the difficulties associated with chronic illnesses.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Informatics Electrical and Electronics Engineering (JIEEE)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
