| Title | Analysis of classification based predicted disease using machine learning and medical things model |
| Publication Type | Conference Paper |
| Year of Publication | 2022 |
| Authors | Bhuyan, Hemanta Kumar, Arun Sai, T., Charan, M., Vignesh Chowdary, K., Brahma, Biswajit |
| Conference Name | 2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) |
| Keywords | Classification algorithms, Data models, Decision trees, deterrence, fuzzy set, gradient decision tree, Heart, Human Behavior, Internet of Medical Things (IoMT), machine learning, Prediction algorithms, Predictive models, pubcrawl, resilience, Resiliency, Scalability |
| Abstract | {Health diseases have been issued seriously harmful in human life due to different dehydrated food and disturbance of working environment in the organization. Precise prediction and diagnosis of disease become a more serious and challenging task for primary deterrence, recognition, and treatment. Thus, based on the above challenges, we proposed the Medical Things (MT) and machine learning models to solve the healthcare problems with appropriate services in disease supervising, forecast, and diagnosis. We developed a prediction framework with machine learning approaches to get different categories of classification for predicted disease. The framework is designed by the fuzzy model with a decision tree to lessen the data complexity. We considered heart disease for experiments and experimental evaluation determined the prediction for categories of classification. The number of decision trees (M) with samples (MS), leaf node (ML), and learning rate (I) is determined as MS=20 |
| DOI | 10.1109/ICAECT54875.2022.9807903 |
| Citation Key | bhuyan_analysis_2022 |
Analysis of classification based predicted disease using machine learning and medical things model