ArticleAnnals of rehabilitation medicine2023
AI in Rehabilitation Medicine: Opportunities and Challenges.
Article in Annals of rehabilitation medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Artificial intelligence in rehabilitation: a living systematic mapping review - first release.European journal of physical and rehabilitation medicine · 2025Pooled it
- Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Effectiveness of AI-assisted rehabilitation for musculoskeletal disorders: a network meta-analysis of pain, range of motion, and functional outcomes.Frontiers in bioengineering and biotechnology · 2025Pooled it
- Toward Precision Cardiac Rehabilitation: Current Limitations and Future Opportunities of Omics and Artificial Intelligence.Sports medicine (Auckland, N.Z.) · 2026Review
- A Multimodal Therapist-Supervised Robotic Gait-Training Platform with Phase-Synchronized Infrared Thermal Biofeedback: A Concept-Level Technical and Translational Healthcare Framework.Healthcare (Basel, Switzerland) · 2026Article
- The Digital Transformation of Rehabilitation Medicine: A Narrative Review of Artificial Intelligence Innovations, Clinical Integration, and Future Paradigms.Journal of evaluation in clinical practice · 2026Review
- Robust Unsupervised Analysis of Longitudinal Functional Trajectories in Older Inpatients Reveals Stable Recovery Profiles: The AIRCOT Study.European journal of investigation in health, psychology and education · 2026Article
- Identifying unique gait phenotypes across neuromotor conditions using wearable inertial sensors and topological data analysis.NPJ digital medicine · 2026Article
- Geriatric rehabilitation in Germany, Austria, and Switzerland (DACH region): a current state analysis.European geriatric medicine · 2026Article
- Artificial intelligence for gait and balance in neurological disorders: a scoping review of clinical applications and technologies.Journal of neurology · 2026Article
- Toward Intelligent Rehabilitation Program Management: A System-Level Review of AI Architectures.Bioengineering (Basel, Switzerland) · 2026Review
- Predicting prosthesis use and mobility needs in lower limb amputees: a machine learning approach using clinical and actigraphy data.Journal of neuroengineering and rehabilitation · 2026Article
- Stroke Rehabilitation, Novel Technology and the Internet of Medical Things.Brain sciences · 2026Review
- Integrating digital health and remote monitoring: emerging trends in cardiac rehabilitation research for chronic heart failure.Frontiers in cardiovascular medicine · 2026Article
- Artificial intelligence in rehabilitation: a review of clinical effectiveness, real-world performance, safety, and equity across modalities and settings.Frontiers in digital health · 2026Review
- Symptoms and causes of obstacles in AI-based telemonitoring: strategies for system development through a CRISP-DM lens.Frontiers in artificial intelligence · 2026Article
- Artificial Intelligence with Robotics for Metabolic Rehabilitation and Enhanced Patient Recovery in Critical Care.Research (Washington, D.C.) · 2026Review
- Toward precision stroke rehabilitation: an integrated causal machine learning and clinician feedback approach.JAMIA open · 2025Article
- The rise and potential opportunities of large language model agents in bioinformatics and biomedicine.Briefings in bioinformatics · 2025Review
- Enhancing home rehabilitation through AI-driven virtual assistants: a narrative review.Annals of translational medicine · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Artificial intelligence (AI) tools are increasingly able to learn from larger and more complex data, thus allowing clinicians and scientists to gain new insights from the information they collect about their patients every day. In rehabilitation medicine, AI can be used to find patterns in huge amounts of healthcare data. These patterns can then be leveraged at the individual level, to design personalized care strategies and interventions to optimize each patient's outcomes. However, building effective AI tools requires many careful considerations about how we collect and handle data, how we train the models, and how we interpret results. In this perspective, we discuss some of the current opportunities and challenges for AI in rehabilitation. We first review recent trends in AI for the screening, diagnosis, treatment, and continuous monitoring of disease or injury, with a special focus on the different types of healthcare data used for these applications. We then examine potential barriers to designing and integrating AI into the clinical workflow, and we propose an end-to-end framework to address these barriers and guide the development of effective AI for rehabilitation. Finally, we present ideas for future work to pave the way for AI implementation in real-world rehabilitation practices.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.