Artificial intelligence in physical and rehabilitation medicine: first update of the living systematic mapping review up to May 31st, 2025
Year: 2026
Type: article
Study design: Systematic Review
Abstract: BACKGROUND: Artificial intelligence is increasingly applied to rehabilitation; however, persisting gaps in research, such as methodological heterogeneity, poor reporting, and lack of validation, reduce clinical translation. Living systematic reviews offer a dynamic approach to continuously monitor evolving evidence. The aim of this first update up to May 31st, 2025 is to expand current evidence base, identifying emerging trends and persistent gaps.METHODS: A total of 784 studies were screened, and 95 new studies were included, for a cumulative total of 335 studies across the first release and the update up to May 31st, 2025.RESULTS: In this update up to May 31st, 2025, 95 new studies were included, bringing the cumulative dataset to 335 studies. A strong recent growth in publications was observed, with China and the USA as the main contributors. There is an increase in the clinical-oriented use of AI. Of note, there is a slight increase in the adoption of reporting guidelines. Methodological limitations persisted, particularly a lack of adoption of reporting tools dedicated to and validated for AI. Explainability remains inconsistently described and applied (28.4%) with a growth trend (+18.2%); and external validation is infrequent (13.7%). Although randomized controlled trials showed a slight increase, they remain underrepresented overall, a finding consistent with the OCEBM distribution, which is still predominantly weighted toward lower-to-moderate levels of evidence (Level 3-4). This highlights persistent gaps in high-quality evidence.CONCLUSIONS: Literature trends of the update of the living systematic mapping review REHALISE up to May 31st, 2025, compared to the first release, suggest a slight and gradual shift toward more clinically oriented applications, though robustness and reproducibility remain critical concerns.
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Ministero della Salute
OpenAlex ID: W7204926700
FWCI:
Cites:
Cited by:
Related to:
