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Multiple Disease Prediction Using ML
Alok Katiyar1, Sajid Ali2, Sameer Ray3
1Dr. Alok Katiyar, Professor, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.
2Sajid Ali, Student, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.
3Sameer Ray, Student, Department of CSE, Galgotias University Greater Noida, Gautam Buddha Nagar, Uttar Pradesh, India.
Manuscript received on 27 March 2023 | Revised Manuscript received on 04 April 2023 | Manuscript Accepted on 15 May 2023 | Manuscript published on 30 May 2023 | PP: 15-18 | Volume-12 Issue-1, May 2023 | Retrieval Number: 100.1/ijrte.A75680512123 | DOI: 10.35940/ijrte.A7568.0512123
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Accurate and on-time analysis of any health-related drawback is vital for the interference and treatment of the sickness. The standard method of diagnosis may not be sufficient in cases of a significant illness. Developing a medical diagnosis system supported by machine learning (ML) algorithms for predicting illnesses will facilitate more accurate diagnoses than the standard methodology. We’ve designed a disease prediction system using ML. A Disease Prediction System using Machine Learning could be a system that predicts sickness based on data or symptoms entered into the system and provides accurate results based on that data. This predictive disease model, utilising machine learning, is completed entirely with the assistance of Learning Machines and the Python programming language, leveraging its Flask Interface and utilising previously offered databases from hospitals to predict the illness.
Keywords: Machine Learning, Disease Prediction, Decision Tree, Random Forest, Symptoms.
Scope of the Article: Machine Learning