首页|Soochow University Reports Findings in Bone Fractures (Fracture risk prediction in diabetes patients based on Lasso feature selection and Machine Learning)
Soochow University Reports Findings in Bone Fractures (Fracture risk prediction in diabetes patients based on Lasso feature selection and Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Bone Diseases and Cond itions - Bone Fractures is the subject of a report. According to news reporting originating in Suzhou, People’s Republic of China, by NewsRx journalists, resear ch stated, “Fracture risk among individuals with diabetes poses significant clin ical challenges due to the multifaceted relationship between diabetes and bone h ealth. Diabetes not only affects bone density but also alters bone quality and s tructure, thereby increases the susceptibility to fractures.” The news reporters obtained a quote from the research from Soochow University, “ Given the rising prevalence of diabetes worldwide and its associated complicatio ns, accurate prediction of fracture risk in diabetic individuals has emerged as a pressing clinical need. This study aims to investigate the factors influencing fracture risk among diabetic patients. We propose a framework that combines Las so feature selection with eight classification algorithms. Initially, Lasso regr ession is employed to select 24 significant features. Subsequently, we utilize g rid search and 5-fold cross-validation to train and tune the selected classifica tion algorithms, including KNN, Naive Bayes, Decision Tree, Random Forest, AdaBo ost, XGBoost, Multi-layer Perceptron (MLP), and Support Vector Machine (SVM). Am ong models trained using these important features, Random Forest exhibits the hi ghest performance with a predictive accuracy of 93.87%. Comparative analysis across all features, important features, and remaining features demons trate the crucial role of features selected by Lasso regression in predicting fr acture risk among diabetic patients.”
SuzhouPeople’s Republic of ChinaAsiaBone Diseases and ConditionsBone FracturesBone ResearchCyborgsEmerging TechnologiesHealth and MedicineMachine LearningRisk and Prevention
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