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TRUVACE RECORD VERSION
record: TRV-2026-2436
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-09T06:01:45.606290Z
status: published
lens: trace
sector: health
headline: The Role of Artificial Intelligence in Treatment Planning in Physical and Rehabilitation Medicine: A Systematic Review
dek: Objective Individualized rehabilitation plans are crucial for maximizing clinical outcomes. Generative artificial intelligence (AI), particularly large language models (LLMs), which can generate new content based on large knowledge bases, could improve personalized rehabilitation. This systematic review aimed to assess accuracy and application of LLMs in rehabilitation. Design A systematic search was conducted in PubMed, Web of Science, and Scopus until February 2026. The PICO included LLMs (P), their use in reh…
gain_title: A systematic review of nine studies found AI chatbot rehabilitation plans reached 98.75% concordance with expert opinion after an expert advisory board reviewed the AI-generated statements.
problem_title: The same review of nine studies found the included studies reported hallucinations from AI chatbots, so their rehabilitation plans needed clinician supervision.
trace_subject: Large language models generating rehabilitation treatment plans
gain_reading: A systematic review of nine studies found AI chatbot rehabilitation plans reached 98.75% concordance with expert opinion after an expert advisory board reviewed the AI-generated statements.
gain_evidence: Concordance with expert opinion varied, reaching 98.75% after an expert advisory board reviewed AI-generated statements.
problem_reading: The same review of nine studies found the included studies reported hallucinations from AI chatbots, so their rehabilitation plans needed clinician supervision.
problem_evidence: the included studies reported hallucinations, underscoring the necessity of supervision
quick_read: A systematic review of nine studies assessed how accurately large language models, the AI chatbots behind tools like ChatGPT, produce rehabilitation treatment plans. Agreement with expert opinion varied across studies and reached 98.75% once an expert advisory board had reviewed the AI-generated statements.

In musculoskeletal and cardiovascular rehabilitation, the chatbots produced plans aligned with clinical guidelines. The included studies also reported hallucinations, meaning the models generated incorrect content, which the authors say makes clinician supervision necessary.

The reviewers searched PubMed, Web of Science and Scopus up to February 2026. They conclude the tools show promise for adaptable, personalised planning, but say higher-quality studies are needed to test real-world effectiveness and define how to implement them.
limitation: The review included only nine studies, and the authors say high-quality studies are still needed to validate real-world effectiveness and define implementation strategies.
tag: Dual reading
key_points: Nine studies met the inclusion criteria after searches of PubMed, Web of Science and Scopus through February 2026. | Concordance with expert opinion varied, with the highest figure at 98.75% after an expert advisory board reviewed the AI statements. | In musculoskeletal and cardiovascular rehabilitation, the chatbots showed alignment with clinical guidelines. | The included studies reported hallucinations, so the authors stress supervision of AI-generated plans. | The comparison was against expert opinion or other AI systems such as machine learning, deep learning or clinical decision support systems. | Methodological quality was assessed with JBI tools, and two reviewers extracted data with a third resolving conflicts.
rundown: The review asked whether large language models can generate appropriate rehabilitation plans that comply with expert clinicians or clinical practice guidelines. It compared them with expert opinion or other AI systems, and excluded studies of non-generative AI.

Across nine included studies, agreement with experts varied. The 98.75% figure came after an expert advisory board reviewed the AI-generated statements, not from unreviewed output alone.

Alignment with guidelines was reported in musculoskeletal and cardiovascular rehabilitation. Hallucinations appeared in the included studies, which the authors say makes supervision necessary.

The authors call the capabilities promising and say they may offer adaptability and personalisation. They add that high-quality studies are needed to validate real-world effectiveness and define implementation strategies.
sources:
- peer_reviewed | American Journal of Physical Medicine & Rehabilitation | https://doi.org/10.1097/phm.0000000000003193 | 2026-11-02
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