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Strategies for disease diagnosis by machine learning techniques

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.

کلیدواژه های Strategies for disease diagnosis by machine learning techniques:

Prediction ، Machine learning ، Classification ، penalized logistic Ridge regression

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