公开(公告)号：US20220076826A1

公开(公告)日：2022-03-10

申请号：US17013661

申请日：2020-09-07

Applicant: Fanxin Zeng ,  Fanwei Zeng ,  Jing Zhu ,  Qianrong Xie ,  Pingxi Wang ,  Yue Chen

Inventor： Fanxin Zeng ,  Fanwei Zeng ,  Jing Zhu ,  Qianrong Xie ,  Pingxi Wang ,  Yue Chen

IPC: G16H50/20 ,  G16H50/30

Abstract: The invention discloses a model based on machine learning-radiomics which is a Nomogram model; the establishment of said Nomogram model comprising following steps: S1. collecting data and predicting factor selection; S2. combining selected 6 radiomics characteristics according to contribution weighting, developing a rad-score model; S3. establishing different diagnosis models, comparing performances of the diagnosis models in the diagnosis of osteoporosis and osteopenia, wherein said diagnosis models comprise: Clinics model, Radiomics model, and Combined model; S4. performing visualization processing on combined model by using the “rms” packet in R software to obtain Nomogram model; S5. validation of the Nomogram model. The invention combines characteristics of the radiomics and clinical risk factors to establish a combined Nomogram model to diagnose conditions of osteoporosis and osteopenia of patients. The diagnosis method can accurately distinct patients with osteoporosis from patients with osteopenia, having great application value for selection of clinical therapeutic regimen.