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Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine

by Akshay Kamath, Amogh Parab, Neeraj Kerkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 41
Year of Publication: 2018
Authors: Akshay Kamath, Amogh Parab, Neeraj Kerkar
10.5120/ijca2018916977

Akshay Kamath, Amogh Parab, Neeraj Kerkar . Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine. International Journal of Computer Applications. 179, 41 ( May 2018), 14-18. DOI=10.5120/ijca2018916977

@article{ 10.5120/ijca2018916977,
author = { Akshay Kamath, Amogh Parab, Neeraj Kerkar },
title = { Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 179 },
number = { 41 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 14-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number41/29354-2018916977/ },
doi = { 10.5120/ijca2018916977 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:03.127429+05:30
%A Akshay Kamath
%A Amogh Parab
%A Neeraj Kerkar
%T Symptom Recommendation using Collaborative Filtering and Disease Prediction using Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 41
%P 14-18
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Early diagnosis and identification of diseases play a vital role in the field of medicine. With the emergence of powerful machine learning techniques, it is now possible to derive greater insights from the available data. This paper discusses how one such machine learning technique can be used to recommend symptoms to users. The proposed system allows users to enter symptoms and uses machine learning techniques to recommend similar symptoms. Another machine learning technique for classification is discussed which is used predict the possibility of having a disease. The results demonstrate the effectiveness of different machine learning techniques on the given data.

References
  1. Portugal, Ivens, Paulo Alencar, and Donald Cowan. "The use of machine learning algorithms in recommender systems: a systematic review." Expert Systems with Applications (2017).
  2. Radhimeenakshi, S. "Classification and prediction of heart disease risk using data mining techniques of Support Vector Machine and Artificial Neural Network." Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on. IEEE, 2016.
  3. Kulev, Igor, et al. "Recommendation algorithm based on collaborative filtering and its application in health care." (2013): 34-38.
  4. Kamkar, Iman, et al. "Stable feature selection for clinical prediction: Exploiting ICD tree structure using Tree-Lasso." Journal of biomedical informatics 53 (2015): 277-290.
  5. Mahajan, Shashank, and Gaurav Shrivastava. "Effective Diagnosis of Diseases through Symptoms Using Artificial Intelligence and Neural Network." International Journal of Engineering Research and Applications: 2248-962.
  6. Prokosch, Hans-Ulrich, and Thomas Ganslandt. "Perspectives for medical informatics." Methods of information in medicine 48.01 (2009): 38-44.
Index Terms

Computer Science
Information Sciences

Keywords

Support Vector Machine Symptom Recommendation Jaccard coefficient Django Electronic medical record Disease prediction

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