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

By Juan Li, PhD
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Output Details

Description
This output is the code used for the analysis of smell test performance from DeNoPa, PROBE and Ottawa Cohort, as reported 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. Authors: 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 Code created by Dr. Juan Li, Ottawa Hospital Research Institute, Canada
Tags
  • Algorithms
  • Analysis
  • Clinical feature
  • Clinical measures
  • Data science
  • Diagnostic
  • Machine learning
  • Olfaction
  • Olfactory dysfunction
  • Parkinson's disease
  • Parkinsonism
Team
Team Schlossmacher
Program
Collaborative Research Network
Theme
Circuitry and Brain-Body Interactions

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