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An explainable predictive machine learning model of osteopenia for perimenopausal women based on clinical data: a retrospective single-center study.

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Title: An explainable predictive machine learning model of osteopenia for perimenopausal women based on clinical data: a retrospective single-center study.
Authors: Zhuo X; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China., Zeng H; Department of Endocrinology, The Second People's Hospital of Foshan, Affiliated Foshan Hospital of Guangdong Pharmaceutical University, Foshan, Guangdong, China., Chen H; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China., Wang Y; Department of Endocrinology, The Second People's Hospital of Foshan, Affiliated Foshan Hospital of Guangdong Pharmaceutical University, Foshan, Guangdong, China., Feng Z; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China., Liang Q; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China.
Source: Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 May 29; Vol. 17, pp. 1817729. Date of Electronic Publication: 2026 May 29 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101555782 Publication Model: eCollection Cited Medium: Print ISSN: 1664-2392 (Print) Linking ISSN: 16642392 NLM ISO Abbreviation: Front Endocrinol (Lausanne) Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: An explainable predictive machine learning model of osteopenia for perimenopausal women based on clinical data: a retrospective single-center study.
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  Data: <searchLink fieldCode="AU" term="%22Zhuo+X%22">Zhuo X</searchLink>; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China.<br /><searchLink fieldCode="AU" term="%22Zeng+H%22">Zeng H</searchLink>; Department of Endocrinology, The Second People's Hospital of Foshan, Affiliated Foshan Hospital of Guangdong Pharmaceutical University, Foshan, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Chen+H%22">Chen H</searchLink>; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China.<br /><searchLink fieldCode="AU" term="%22Wang+Y%22">Wang Y</searchLink>; Department of Endocrinology, The Second People's Hospital of Foshan, Affiliated Foshan Hospital of Guangdong Pharmaceutical University, Foshan, Guangdong, China.<br /><searchLink fieldCode="AU" term="%22Feng+Z%22">Feng Z</searchLink>; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China.<br /><searchLink fieldCode="AU" term="%22Liang+Q%22">Liang Q</searchLink>; Department of Clinical Laboratory, The First People's Hospital of Foshan (Foshan Hospital Affiliated to Southern University of Science and Technology), School of Medicine, Southern University of Science and Technology, Foshan, Guangdong, China.; Foshan Key Laboratory of Skin Tissue Engineering and Precision Diagnosis and Treatment of Infectious Skin Diseases, Foshan, China.
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  Data: <searchLink fieldCode="JN" term="%22101555782%22">Frontiers in endocrinology</searchLink> [Front Endocrinol (Lausanne)] 2026 May 29; Vol. 17, pp. 1817729. <i>Date of Electronic Publication: </i>2026 May 29 (<i>Print Publication: </i>2026).
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        Value: 10.3389/fendo.2026.1817729
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        Text: English
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