ReviewJournal of Parkinson's disease2026
Harnessing artificial intelligence: Revolutionizing clinical care for Parkinson's disease.
Review in Journal of Parkinson's disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the use of artificial intelligence (AI) in healthcare becomes more pervasive, its application in the clinical care for those with Parkinson's disease (PD) presents exciting opportunities to improve the timeliness and accuracy of diagnosis and to optimize treatment. Perhaps more than many other neurological conditions, PD lends itself to the creation of rich data from which AI can surface actionable insights that hold the potential to revolutionize PD care in a personalized manner. For direct clinical care, AI has the potential to contribute to initial diagnosis, disease subtyping, symptom identification and severity assessment, progression monitoring, and treatment management. With patients and clinicians informing AI and contributing to its methods of deployment, an enormous opportunity exists to open up access to expert-level care to many more people.
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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 Socratic graph.