Evidence map›Paper›PMID 37946764›Full record

ArticleWorld journal of clinical cases2023

Artificial intelligence and machine learning in motor recovery: A rehabilitation medicine perspective.

Raktim Swarnakar, Shiv Lal Yadav

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in World journal of clinical cases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Advances in Artificial Intelligence for Wrist Joint Injury Diagnosis.International journal of medical sciences · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Raktim SwarnakarDepartment of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India. raktimswarnakar@hotmail.com.
Shiv Lal YadavDepartment of Physical Medicine and Rehabilitation, All India Institute of Medical Sciences, New Delhi 110029, Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) and machine learning (ML) are powerful technologies with the potential to revolutionize motor recovery in rehabilitation medicine. This perspective explores how AI and ML are harnessed to assess, diagnose, and design personalized treatment plans for patients with motor impairments. The integration of wearable sensors, virtual reality, augmented reality, and robotic devices allows for precise movement analysis and adaptive neurorehabilitation approaches. Moreover, AI-driven telerehabilitation enables remote monitoring and consultation. Although these applications show promise, healthcare professionals must interpret AI-generated insights and ensure patient safety. While AI and ML are in their early stages, ongoing research will determine their effectiveness in rehabilitation medicine.

Indexed as

Artificial intelligenceMachine learningMotor learningMotor recoveryPhysical medicine and rehabilitationRehabilitation

Identifiers

PMID37946764
PMCPMC10631394

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.