Use of natural language processing tools in musculoskeletal disability assessment: generating reports and calculating impairment percentages in Turkish health commission settings.
Purpose: This study explores the potential of Natural Language Processing (NLP) tools, specifically ChatGPT-4o and Data Analyst, in supporting health commissions with disability assessments. Methods: Nine realistic patient scenarios were created to reflect typical cases in disability evaluations, en...
| Publicado en: | Disability & Rehabilitation: Assistive Technology Vol. 21; no. 6; pp. 2859 - 2870 |
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| Autores principales: | , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Aug2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=196565043&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 196565043 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17483107 1X04 jtl: Disability & Rehabilitation: Assistive Technology issn: 17483107 maglogo: Y pubinfo: dt: Aug2026 vid: 21 iid: 6 pid: 377 pub: Taylor & Francis Ltd place: Philadelphia, Pennsylvania artinfo: ui: 196565043 192715654 196565043 196565043 10.1080/17483107.2026.2653070 196565043 ppf: 2859 ppct: 11 formats: tig: atl: Use of natural language processing tools in musculoskeletal disability assessment: generating reports and calculating impairment percentages in Turkish health commission settings. aug: au: Duman Şahin, Zehra Altuntaş, Vedat Yılmaz Muluk, Selkin affil: Department of Physical Medicine and Rehabilitation, Ministry of Health Antalya City Hospital, Antalya, Turkey sug: subj: Natural Language Processing Utilization Disability Evaluation Artificial Intelligence, Generative Utilization Decision Support Techniques Utilization Human Turkiye Stroke Cerebral Palsy Hereditary Diseases Cross Sectional Studies Meningitis Cerebral Ischemia Hematoma, Subdural Data Analysis Software Descriptive Statistics ab: Purpose: This study explores the potential of Natural Language Processing (NLP) tools, specifically ChatGPT-4o and Data Analyst, in supporting health commissions with disability assessments. Methods: Nine realistic patient scenarios were created to reflect typical cases in disability evaluations, encompassing conditions like stroke, cerebral palsy, traumatic injuries, and hereditary disorders, each involving varied motor and functional impairments. These scenarios were input into ChatGPT-4o and Data Analyst. Their outputs were evaluated using a 5-point Likert scale on alignment with expert guidelines, completeness, and lack of false information. Interrater reliability was established before scoring. Results: Both models produced generally high-quality narrative reports, ChatGPT-4o was rated "very good" and Data Analyst "good," with no statistically significant difference in overall scores. However, ChatGPT-4o failed to calculate correct disability percentages in 55.6%, and Data Analyst failed in 88.9% of scenarios. Conclusions: While NLP tools can assist in generating structured disability reports, they currently lack the precision needed for calculating disability percentages reliably. Expert oversight remains essential for decision-making in disability assessments. IMPLICATIONS FOR REHABILITATION: Natural Language Processing (NLP) tools like ChatGPT-4o can reduce physician burden by generating narrative disability reports. These models currently lack the reliability for unsupervised use in calculating disability percentages. NLP-assisted documentation may streamline multidisciplinary commission work but requires expert validation. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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