High-Throughput CSF Proteomics and Machine Learning to Identify Proteomic Signatures for Parkinson Disease Development and Progression.

Kazuto TsukitaHaruhi Sakamaki-TsukitaSergio KaiserLuqing ZhangMirko MessaPablo Serrano-FernandezRyosuke Takahashi

Published in: Neurology (2023)

This study provides Class II evidence that the CSF proteome contains clinically important information regarding the development and progression of Parkinson disease that can be deciphered by a combination of high-throughput proteomics and machine learning.

Keyphrases

parkinson disease
high throughput
machine learning
deep brain stimulation
mass spectrometry
label free
single cell
artificial intelligence
big data
gene expression
cerebrospinal fluid
health information