ReviewJournal of Parkinson's disease
Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson's Disease?
Review in Journal of Parkinson's disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 17 citations in OpenAlex.
- The future digital outpatient clinic for movement disorders: from technological innovation to ethical and systemic implementation-a position paper.Journal of neural transmission (Vienna, Austria : 1996) · 2026Review
- AI-Driven Advances in Parkinson's Disease Neurosurgery: Enhancing Patient Selection, Trial Efficiency, and Therapeutic Outcomes.Brain sciences · 2025Review
- Diverse preferences, different solutions: Exploring remote monitoring preferences in Parkinson's disease through a discrete choice experiment.Journal of Parkinson's disease · 2025Article
- The Role of Wearable Devices in Chronic Disease Monitoring and Patient Care: A Comprehensive Review.Cureus · 2024Review
- Article
- Article
- A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson's Disease: Past Studies and Future Perspectives.Diagnostics (Basel, Switzerland) · 2022Review
- Imperative Role of Machine Learning Algorithm for Detection of Parkinson's Disease: Review, Challenges and Recommendations.Diagnostics (Basel, Switzerland) · 2022Review
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 at 2 institutions in 1 country.
Funding
Abstract
The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can offer otherwise unobtainable insights about disease burden and patient status in a free-living environment. Moreover, from clinical datasets AI can improve patient symptom monitoring and global epidemiologic efforts. While these applications are exciting, it is necessary to examine both the utility and limitations of these novel analytic methods. The most promising uses of AI remain aspirational. For example, defining the molecular subtypes of Parkinson's disease will be assisted by future applications of AI to relevant datasets. This will allow clinicians to match patients to molecular therapies and will thus help launch precision medicine. Until AI proves its potential in pushing the frontier of precision medicine, its utility will primarily remain in individualized monitoring, complementing but not replacing movement disorders specialists.
Indexed as
Identifiers
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.