Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Mobile phone applications in Parkinson's disease: a systematic review
Detecting and monitoring the symptoms of Parkinson's disease using smartphones: A pilot study
Pharmacological treatment of Parkinson disease: a review.
"There's a Pain App for That": Review of Patient-targeted Smartphone Applications for Pain Management.
Free-living monitoring of Parkinson's disease: Lessons from the field
Nonpharmacological treatments for patients with Parkinson's disease
A review of Parkinson's disease.
A Systematic Review of Healthcare Applications for Smartphones
Biomarkers in Parkinson's disease: Advances and strategies
Parkinson's Disease Motor Symptoms in Machine Learning: A Review
Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review
Effectiveness of acupuncture for Parkinson's disease: A systematic review
Apathy in untreated, de novo patients with Parkinson’s disease: validation study of Apathy Evaluation Scale
A Systematic Review on Mobile Health Care
Usability and clinical efficacy of diabetes mobile applications for adults with type 2 diabetes: A systematic review.
A review of presented mathematical models in Parkinson’s disease: black- and gray-box models
Current understanding of the molecular mechanisms in Parkinson's disease: Targets for potential treatments
Quantitative wearable sensors for objective assessment of Parkinson's disease
Improved spiral test using digitized graphics tablet for monitoring Parkinson's disease
Prediagnostic presentations of Parkinson's disease in primary care: a case-control study
Towards a Framework for Evaluating Mobile Mental Health Apps.
Quantitative wearable sensors for objective assessment of Parkinson's disease
Centralities in Large Networks: Algorithms and Observations
An implementation of the earliest deadline first algorithm in Linux
A 2.1 MHz Crystal Oscillator Time Base with a Current Consumption under 500 nA
Text zone classification using unsupervised feature learning