Strategies for disease diagnosis by machine learning techniques
محل انتشار: مجله مدلسازی ریاضی، دوره: 11، شماره: 3
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 90
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شناسه ملی سند علمی:
JR_JMMO-11-3_002
تاریخ نمایه سازی: 19 خرداد 1403
چکیده مقاله Strategies for disease diagnosis by machine learning techniques
Machine learning (ML) techniques have become a point of interest in medical research. To predict the existence of a specified disease, two methods K-Nearest Neighbors (KNN) and logistic regression can be used, which are based on distance and probability, respectively. These methods have their problems, which leads us to use the ideas of both methods to improve the prediction of disease outcomes. For this sake, first, the data is transformed into another space based on logistic regression. Next, the features are weighted according to their importance in this space. Then, we introduce a new distance function to predict disease outcomes based on the neighborhood radius. Lastly, to decrease the CPU time, we present a partitioning criterion for the data.
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نویسندگان مقاله Strategies for disease diagnosis by machine learning techniques
Elham Hafezieh
University of Mazandaran, Babolsar, Iran
Ali Tavakoli
University of Mazandaran, Babolsar, Iran
Mashaallah Matinfar
University of Mazandaran, Babolsar, Iran