Classification of Parkinson's disease and its stages using machine learning
JM Templeton, C Poellabauer, S Schneider - Scientific reports, 2022 - nature.com
As digital health technology becomes more pervasive, machine learning (ML) provides a
robust way to analyze and interpret the myriad of collected features. The purpose of this …
robust way to analyze and interpret the myriad of collected features. The purpose of this …
A Comprehensive Multifunctional Approach for Measuring Parkinson's Disease Severity
Objectives This research study aims to advance the staging of Parkinson's disease (PD) by
incorporating machine learning to assess and include a broader multifunctional spectrum of …
incorporating machine learning to assess and include a broader multifunctional spectrum of …
Towards symptom-specific intervention recommendation systems
JM Templeton, C Poellabauer… - Journal of Parkinson's …, 2022 - content.iospress.com
Background: Mobile devices and their capabilities (eg, device sensors and human-device
interactions) are increasingly being considered for use in clinical assessments and disease …
interactions) are increasingly being considered for use in clinical assessments and disease …
Beyond Motor Symptoms: Toward a Comprehensive Grading of Parkinson's Disease Severity
This study applies machine learning (ML) feature analysis to an array of multi-functional
neurocognitive symptoms specific to individuals with Parkinson's Disease (PD). We provide …
neurocognitive symptoms specific to individuals with Parkinson's Disease (PD). We provide …
[图书][B] Towards a Comprehensive Mobile-Based Neurocognitive Digital Health Assessment System (NDHAS)
JM Templeton - 2022 - search.proquest.com
Staging methods and clinical assessments including the Hoehn and Yahr Scale (H&Y), MDS-
Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Dean-Woodcock …
Unified Parkinson's Disease Rating Scale (MDS-UPDRS), Dean-Woodcock …