Multi Disease Prediction System By using Machine Learning
Year: 2025
Type: article
Abstract: In the last few years, machine learning has really changed the game in healthcare, especially when it comes to predicting diseases. This study introduces a multi-disease prediction model that helps identify the risk of a bunch of diseases at once, using a mix of factors like patient demographics, clinical history, genetic background, and lifestyle choices. By tapping into powerful classification algorithms and data mining tricks, the model dives deep into complex healthcare data and predicts the chances of diseases like heart conditions, diabetes, cancer, and neurological issues. It pulls together a variety of data sources, including electronic health records (EHRs), medical images, and symptoms reported by patients, to give accurate predictions that can really help healthcare pros with early diagnoses and personalized treatment plans. We check out how well the model performs using cross-validation techniques, and it shows impressive accuracy, sensitivity, and specificity, making it a handy tool for preventive care and decision support systems. Finally, this approach is all about boosting early intervention strategies and easing the load on healthcare systems by allowing for a more proactive and precise way to manage diseases.
Authors: Bhosale, Prof. Santosh, Payale, Gargi, Tupare, Anushka, Mane, Sarthak
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W6968166406
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