Dataset for: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

By Juan Li, PhD, Brit Mollenhauer , MD and Michael Schlossmacher, MD
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Output Details

Description
This file contains smell test performance datasets analyzed in the study: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation Juan Li, Kelsey Grimes, Joseph Saade, Julianna J. Tomlinson, Tiago A. Mestre, Sebastian Schade, Sandrina Weber, Mohammed Dakna, Tamara Wicke, Elisabeth Lang, Claudia Trenkwalder, Natalina Salmaso, Andrew Frank, Tim Ramsay, Douglas Manuel, aSCENT-PD Investigators, Brit Mollenhauer, Michael G. Schlossmacher medRxiv 2024.08.09.24311696; doi: https://doi.org/10.1101/2024.08.09.24311696
Team
Team Schlossmacher
Program
Collaborative Research Network
Theme
Circuitry and Brain-Body Interactions

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Related Research

Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

Reduced olfaction is a common feature of typical Parkinson disease (PD) and dementia with Lewy bodies (DLB). We have created a simplified smell test based on seven specific odorants that can distinguish PD/DLB patients from healthy controls.

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Code for analysis of smell test dataset included in: Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation

Code used for the analysis of smell test performance as reported in "Development of a Simplified Smell Test to Identify Patients with Typical Parkinson’s as Informed by Multiple Cohorts, Machine Learning and External Validation", Li et al., 2024

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