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DTPOS provides a sensitivity of 92.3% and a positive predictive value of 82.8%, which might be used to rule in subjects at risk of osteopenia and osteoporosis in a community-based screening as it is simple to conduct. The age of 58 years and weight at a cutoff of 57.8 kg were the essential predictors of our tool. The Decision Tree for Postmenopausal Osteoporosis Screening (DTPOS) tool was developed from the best performance of CHAID’s algorithms. The optimal model is selected according to the performance of blind data testing and compared with traditional screening tools: Osteoporosis Self-Assessment for Asians and the Khon Kaen Osteoporosis Study. Each algorithm possesses its characteristic performance. The investigation revealed that the DT algorithms have insignificantly different performances regarding the accuracy, sensitivity, specificity, and area under the curve. Four DT algorithms, namely, classification and regression tree chi-squared automatic interaction detection (CHAID) quick, unbiased, efficient statistical tree and C4.5, were implemented on 356 patients, of whom 266 were abnormal and 90 normal. This study constructs and confirms an osteoporosis screening tool-based decision tree (DT) model. Fb analityca tidak hanya langsung mendapatkan data real calon konsumen dari Facebook (nama, gender, lokasi,email, Nomor Handphone) tetapi dengan simply interest mampu menunjukkan interest secara tepat sesuai target audiens Anda. Hadir dengan update Besar-besaran mengikuti algoritma facebook terbaru. Osteoporosis is still a serious public health issue in Thailand, particularly in postmenopausal women meanwhile, new effective screening tools are required for rapid diagnosis. Tools ini sudah bisa Anda miliki sekarang juga.
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