An Intelligent Healthcare System for Diagnosis Based on Machine Learning Technique
Lakshita Aggarwal, Puneet Goswami, Shivani Batra, Sana Alam, Arvind Kumar, Prakash Srivastava
Abstract
In today's stop-and-go development; data is growing enormously at a fast rate in fields like healthcare, agriculture, businesses, and many more. The vast amount of data needs to be accessed and integrated intelligently to support better health care delivery, smart activities using the resources judiciously, and many more. Big data makes data smart by measuring and monitoring processes efficiently and facilitating a streamlined workflow of data more deeply which would improve patient care efficiently using past health records. Systematic analysis of extensive data can help to detect patterns so that better serving of patients can take place and protect health outcomes in a better way. Digital networks can bring together patterns and knowledge sharing delivering content development. Machine learning can facilitate learning more accurately than humans as it is data-driven. In this paper, we tried to focus on the machine learning model to train the data. So, as to observe and improve the accuracy of the data model applied. The real Covid data of patients are being collected from the HIMSR hospital in New Delhi. The data is being analyzed and trained using a machine learning model for better prediction and accuracy.