Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction

Year : 2025 | Volume : 16 | Issue : 01 | Page : 1-6
    By

    Ankit Sharma,

  • A.N. Kshirsagar,

  • Anish Kannawar,

  • Abhishek Mishra,

  1. Student, Department of Electronics and Telecommunication Engineering, Smt. Kashibai Navale College of Engineering (affiliated to Savitribai Phule Pune University), Vadgaon, Pune, Maharashtra, India
  2. Professor, Department of Electronics and Telecommunication Engineering, Smt. Kashibai Navale College of Engineering (affiliated to Savitribai Phule Pune University), Vadgaon, Pune, Maharashtra, India
  3. Student, Department of Electronics and Telecommunication Engineering, Smt. Kashibai Navale College of Engineering (affiliated to Savitribai Phule Pune University), Vadgaon, Pune, Maharashtra, India
  4. Professor and Head, Department of Electronics and Telecommunication Engineering, Smt. Kashibai Navale College of Engineering (affiliated to Savitribai Phule Pune University), Vadgaon, Pune, Maharashtra, India

Abstract

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The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. To train and assess the prediction models, a variety of machine learning methods were used, including k-Nearest Neighbors (k-NN), Random Forest, Decision Trees, and Support Vector Machines (SVM). The primary objective was to enhance healthcare by providing timely and accurate predictions for conditions such as diabetes, heart disease, cancer, and respiratory illnesses. A user-friendly interface for medical practitioners incorporates the predictive models that are produced.

Keywords: Machine learning, disease prediction, predictive modeling, decision trees, random forest, support vector machines, k-nearest neighbors

[This article belongs to Journal of Electronic Design Technology ]

How to cite this article:
Ankit Sharma, A.N. Kshirsagar, Anish Kannawar, Abhishek Mishra. Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction. Journal of Electronic Design Technology. 2025; 16(01):1-6.
How to cite this URL:
Ankit Sharma, A.N. Kshirsagar, Anish Kannawar, Abhishek Mishra. Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction. Journal of Electronic Design Technology. 2025; 16(01):1-6. Available from: https://journals.stmjournals.com/joedt/article=2025/view=0



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Regular Issue Subscription Original Research
Volume 16
Issue 01
Received 23/12/2024
Accepted 01/02/2025
Published 08/02/2025
Publication Time 47 Days
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