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Review on Different Algorithms for Disease Prediction
Subject area: Science,Engineering and Technology · Area of research: Machine learning
Abstract
Any health-related concern must be accurately and promptly examined to prevent and treat illness. The traditional diagnostic approach might not be sufficient in the case of a serious illness. A diagnosis that is made using machine learning (ML) can be more accurate than one made using conventional methods in the construction of a medical diagnosis system for disease prediction. Supervised machine learning (ML) algorithms have shown tremendous potential in outperforming traditional systems for illness diagnosis, aiding medical personnel in the early detection of high-risk disorders.This study discusses a number of algorithms that can be employed to identify diseases based on the patient's current symptoms.We also provide a summary of the outcomes produced by the various algorithms.
Keywords
Machine learning, Decision Tree Classifier, Random Forest Classifier, Na?ve Bayes Classifier, Support Vector Machine, K-Nearest Neighbors, ID3
References
[1] Ferjani, Marouane (2020) “Disease Prediction Using Machine Learning”. 10.13140/RG.2.2.18279.47521.
[2] P. Jha, T. Biswas, U. Sagar and K. Ahuja, "Prediction with ML paradigm in Healthcare System," 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), 2021, pp. 1334-1342, doi: 10.1109/ICESC51422.2021.9532752.
[3] Md. Ehtisham Farooqui, Dr. Jameel Ahmad, “Disease Prediction System using Support Vector Machine and Multilinear Regression”, International Journal of Innovative Research in Computer Science & Technology (IJIRCST) ISSN: 2347-5552, Volume- 8, Issue- 4, July- 2020.
[4] Sarthak Khurana1, Atishay Jain, Shikhar Kataria, Kunal Bhasin, Sunny Arora, “Disease Prediction System”, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056.
[5] Ahelam Tikotikar, Mallikarjun Kodabagi, “A SURVEY ON TECHNIQUE FOR PREDICTION OF DISEASE IN MEDICAL DATA”, 2017 International Conference On Smart Technology for Smart Nation.
[6] Sneha Grampurohit, Chetan Sagarnal, “Disease Prediction using Machine Learning Algorithms”, 2020 International Conference for Emerging Technology (INCET) .
[7] Kunal Takke, Rameez Bhaijee, Avanish Singh, Mr. Abhay Patil, “Medical Disease Prediction using Machine Learning Algorithms”, International Journal for Research in Applied Science & Engineering Technology (IJRASET) Volume 10 Issue V May 2022.
[8] Palle Pramod Reddy, Dirisinala Madhu Babu, Hardeep Kumar, Dr.Shivi Sharma, “Disease Prediction using Machine Learning”, Volume 9, Issue 5 May 2021 |
How to cite this paper
@article{1704283,
author = {Om Khedkar, Rutuja Labhshetwar, Jayant Khandebharad, Vaishnavi Dhakare, Prof. Parag Jambhulkar},
title = {Review on Different Algorithms for Disease Prediction},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {6},
number = {10},
pages = {475-478},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1704283.pdf},
abstract = {Any health-related concern must be accurately and promptly examined to prevent and treat illness. The traditional diagnostic approach might not be sufficient in the case of a serious illness. A diagnosis that is made using machine learning (ML) can be more accurate than one made using conventional methods in the construction of a medical diagnosis system for disease prediction. Supervised machine learning (ML) algorithms have shown tremendous potential in outperforming traditional systems for illness diagnosis, aiding medical personnel in the early detection of high-risk disorders.This study discusses a number of algorithms that can be employed to identify diseases based on the patient's current symptoms.We also provide a summary of the outcomes produced by the various algorithms.},
keywords = {Machine learning, Decision Tree Classifier, Random Forest Classifier, Na?ve Bayes Classifier, Support Vector Machine, K-Nearest Neighbors, ID3},
month = {April},
}