Machine learning to improve analysis of disability in electronic health records: an untapped opportunity for health inequities research.
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| Title: | Machine learning to improve analysis of disability in electronic health records: an untapped opportunity for health inequities research. |
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| Authors: | Rotenberg S; International Centre for Evidence in Disability, London School of Hygiene and Tropical Medicine, London, UK. Electronic address: sara.rotenberg@lshtm.ac.uk., Mesinovic M; Department of Engineering Science, University of Oxford, Oxford, UK., Saloniki EC; Global Business School for Health, University College London (UCL), London, UK., Chen S; International Centre for Evidence in Disability, London School of Hygiene and Tropical Medicine, London, UK., Raine R; Department of Primary Care and Population Health, University College London (UCL), London, UK., Kuper H; International Centre for Evidence in Disability, London School of Hygiene and Tropical Medicine, London, UK. |
| Source: | Disability and health journal [Disabil Health J] 2026 Apr; Vol. 19 (2), pp. 102017. Date of Electronic Publication: 2025 Dec 18. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Country of Publication: United States NLM ID: 101306633 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1876-7583 (Electronic) Linking ISSN: 18767583 NLM ISO Abbreviation: Disabil Health J Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1876-7583 |
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| DOI: | 10.1016/j.dhjo.2025.102017 |
