Smart Healthcare Prediction Using Machine Learning

Smart Healthcare Prediction Using Machine Learning

Mrs. Adithi M1, Pavan Kumar R2, Priya Y S3, Sneha B S4, Vaishnavi O5

1Assistant Professor,2Final year Student, 3Final year Student, 4Final year Student, 5Final year Student,

Department of Electronics and Communication Engineering P E S Institute of technology and management, Shimoga

Abstract - In this paper, the utilization of machine learning techniques in the healthcare system is introduced. As the healthcare industry generates increasingly vast amounts of data daily, manual processing by humans becomes impractical for prompt disease diagnosis and treatment decisions. To address this challenge, data management techniques and machine learning algorithms are explored in healthcare applications to facilitate more accurate decision-making processes. Detailed descriptions of medical data are provided, enhancing various facets of healthcare applications through the adoption of this cutting-edge technology. Naïve Bayes machine learning algorithm is employed to train the machine for predicting various diseases, extracting new patterns from extensive datasets to enable predictive analysis and derive knowledge linked to these patterns. A key focus lies in acquiring data automatically or semi-automatically, highlighting the significance of this process.

Key Words:  Machine Learning, Healthcare, Naïve Bayes Algorithm, Predictive Models, Data prediction.