Feasible Prediction of Multiple Diseases using Machine Learning
Automated Multiple Disease Prediction System using Machine Learning is an advanced healthcare application that utilizes machine learning algorithms to accurately predict the likelihood of a patient having multiple diseases based on their medical history and symptoms. The system employs a comprehensi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2023-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01051.pdf |
| _version_ | 1797658759556759552 |
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| author | Ramesh Banoth Srinivas G. Ram Praneeth Reddy P. Huraib Rasool M.D. Rawat Divya Sundaray Madhulita |
| author_facet | Ramesh Banoth Srinivas G. Ram Praneeth Reddy P. Huraib Rasool M.D. Rawat Divya Sundaray Madhulita |
| author_sort | Ramesh Banoth |
| collection | DOAJ |
| description | Automated Multiple Disease Prediction System using Machine Learning is an advanced healthcare application that utilizes machine learning algorithms to accurately predict the likelihood of a patient having multiple diseases based on their medical history and symptoms. The system employs a comprehensive dataset of medical records and symptoms of various diseases, which are then analysed using machine learning techniques such as decision trees, support vector machines, and random forests. The system’s predictions are highly accurate, and it can assist medical professionals in making more informed decisions and providing better treatment plans for patients. Ultimately, the viable Multiple Disease Prediction System using Machine Learning has the potential to improve healthcare outcomes and reduce healthcare costs by predicting and preventing disease early. |
| first_indexed | 2024-03-11T18:03:54Z |
| format | Article |
| id | doaj.art-28cd12f9a8c741889b730539f50bcfcd |
| institution | Directory Open Access Journal |
| issn | 2267-1242 |
| language | English |
| last_indexed | 2024-03-11T18:03:54Z |
| publishDate | 2023-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj.art-28cd12f9a8c741889b730539f50bcfcd2023-10-17T08:47:10ZengEDP SciencesE3S Web of Conferences2267-12422023-01-014300105110.1051/e3sconf/202343001051e3sconf_icmpc2023_01051Feasible Prediction of Multiple Diseases using Machine LearningRamesh Banoth0Srinivas G.1Ram Praneeth Reddy P.2Huraib Rasool M.D.3Rawat Divya4Sundaray Madhulita5Department of CSE (AI & ML), GRIETDepartment of CSE (AI & ML), GRIETDepartment of CSE (AI & ML), GRIETDepartment of CSE (AI & ML), GRIETUttaranchal Institute of Technology, Uttaranchal UniversityKG Reddy College of Engineering & TechnologyAutomated Multiple Disease Prediction System using Machine Learning is an advanced healthcare application that utilizes machine learning algorithms to accurately predict the likelihood of a patient having multiple diseases based on their medical history and symptoms. The system employs a comprehensive dataset of medical records and symptoms of various diseases, which are then analysed using machine learning techniques such as decision trees, support vector machines, and random forests. The system’s predictions are highly accurate, and it can assist medical professionals in making more informed decisions and providing better treatment plans for patients. Ultimately, the viable Multiple Disease Prediction System using Machine Learning has the potential to improve healthcare outcomes and reduce healthcare costs by predicting and preventing disease early.https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01051.pdf |
| spellingShingle | Ramesh Banoth Srinivas G. Ram Praneeth Reddy P. Huraib Rasool M.D. Rawat Divya Sundaray Madhulita Feasible Prediction of Multiple Diseases using Machine Learning E3S Web of Conferences |
| title | Feasible Prediction of Multiple Diseases using Machine Learning |
| title_full | Feasible Prediction of Multiple Diseases using Machine Learning |
| title_fullStr | Feasible Prediction of Multiple Diseases using Machine Learning |
| title_full_unstemmed | Feasible Prediction of Multiple Diseases using Machine Learning |
| title_short | Feasible Prediction of Multiple Diseases using Machine Learning |
| title_sort | feasible prediction of multiple diseases using machine learning |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2023/67/e3sconf_icmpc2023_01051.pdf |
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