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- W4382052811 abstract "Machine learning technology has been applied in the medical field, which can assist in disease prediction, condition analysis, and assist doctors in judging drug matching. With the change of lifestyle and the improvement of living standards, diabetes has become a high-incidence chronic disease worldwide. In the early stages of diabetes, patients are not easily aware of multiple complications that can eventually lead to more serious disease. In this paper, an Adaptive Weighted Decision Forest(AWDF) algorithm is proposed to analyze human vital condition data and examination data, to analyze and predict diabetes and its complications, and guide diabetes patients to prevent and intervene in advance. The results show that the accuracy and recall of the AWDF method proposed in this paper are higher than those of the single machine learning algorithm model." @default.
- W4382052811 created "2023-06-27" @default.
- W4382052811 creator A5009793323 @default.
- W4382052811 date "2023-04-26" @default.
- W4382052811 modified "2023-09-26" @default.
- W4382052811 title "A Study of Diabetes Prediction Based on Adaptive Weighted Decision Forest" @default.
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- W4382052811 doi "https://doi.org/10.1109/icccbda56900.2023.10154670" @default.
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