Abstract: Breast cancer is among leading reasons for the deaths of women globally. Machine learning techniques can help to classify breast cancer based on some features. In order to find a systematic ...
Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging (DTI) to ...
Objective Early prediction of long-term outcomes in patients with systemic lupus erythematosus (SLE) remains a great challenge in clinical practice. Our study aims to develop and validate predictive ...
Abstract: The research examines the Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) machine learning algorithms with the goal of using machine learning to detect malware and mitigate ...
Objectives To compare the prediction effects of six models based on machine learning theories, which can provide a methodological reference for predicting the risk of type 2 diabetes mellitus (T2DM).
Accurate prediction of compressive strength of concrete is one of the key issues in the concrete industry. In this paper, a prediction method of fly ash-slag concrete compressive strength based on ...
Background: Elderly patients undergoing hip fracture repair surgery are at increased risk of delirium due to aging, comorbidities, and frailty. But current methods for identifying the high risk of ...
aCentre for Clinical Research and Biostatistics, Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong SAR ...
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