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
View Published Dataset

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

Meet the Authors

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.

View Article

Development of a simplified smell test to identify Parkinson’s disease using multiple cohorts, machine learning and item response theory

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.

View Article

Extracellular space diffusion modelling identifies distinct functional advantages of archetypical glutamatergic and GABAergic synapse geometries

We modelled extracellular diffusion in super-resolved images of live brain tissue neuropil. We found that extracellular space geometry shapes local diffusion and this has functional implications for signaling arising from synaptic spill-over.

View Article
View More Outputs
Aligning Science Across Parkinson's
Powered by  GDPR Cookie Compliance
Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.