Identification of BMI-related high-risk feature combinations for diabetes among young adults with normal baseline fasting plasma glucose using interpretable machine learning: a health check-up cohort study.
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| Title: | Identification of BMI-related high-risk feature combinations for diabetes among young adults with normal baseline fasting plasma glucose using interpretable machine learning: a health check-up cohort study. |
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| Authors: | Xu Z; Nursing Department, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China., Zhang Y; Nursing Department, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China., Zhang H; Nursing Department, Longhua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China. |
| Source: | Frontiers in endocrinology [Front Endocrinol (Lausanne)] 2026 May 15; Vol. 17, pp. 1850071. Date of Electronic Publication: 2026 May 15 (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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