Prediction of femoral osteoporosis using machine-learning analysis with radiomics features and abdomen-pelvic CT: A retrospective single center preliminary study

Osteoporosis has increased and developed into a serious public health concern worldwide. Despite the high prevalence, osteoporosis is silent before major fragility fracture and the osteoporosis screening rate is low. Abdomen-pelvic CT (APCT) is one of the most widely conducted medical tests. Artific...

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Veröffentlicht in:	PloS one 2021-03, Vol.16 (3), p.e0247330-e0247330
Hauptverfasser:	Lim, Hyun Kyung, Ha, Hong Il, Park, Sun-Young, Han, Junhee
Format:	Artikel
Sprache:	eng
Schlagworte:	Age Algorithms Biology and Life Sciences Biomedical materials Computer and Information Sciences Diagnosis Disease Drafting software Editing Electronic mail Engineering and Technology Feature selection Femur Fractures Funding Health aspects Hospitals Learning algorithms Machine learning Medical imaging Medicine and Health Sciences Metastasis Methodology Older people Osteoporosis Patients Performance evaluation Performance prediction Physiological aspects Public health Radiology Radiomics Research and Analysis Methods Research facilities Statistical analysis
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