Your browser doesn't support javascript.
loading
Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning.
Bargiotas, Ioannis; Kalogeratos, Argyris; Limnios, Myrto; Vidal, Pierre-Paul; Ricard, Damien; Vayatis, Nicolas.
Affiliation
  • Bargiotas I; Centre Borelli CNRS INSERM, ENS Paris-Saclay, Paris-Saclay University, Gif-sur-Yvette, France.
  • Kalogeratos A; Centre Borelli CNRS INSERM, Université de Paris, Paris, France.
  • Limnios M; Centre Borelli CNRS INSERM, ENS Paris-Saclay, Paris-Saclay University, Gif-sur-Yvette, France.
  • Vidal PP; Centre Borelli CNRS INSERM, Université de Paris, Paris, France.
  • Ricard D; Centre Borelli CNRS INSERM, ENS Paris-Saclay, Paris-Saclay University, Gif-sur-Yvette, France.
  • Vayatis N; Centre Borelli CNRS INSERM, Université de Paris, Paris, France.
PLoS One ; 16(2): e0246790, 2021.
Article in En | MEDLINE | ID: mdl-33630865
Subject(s)
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Accidental Falls / Parkinsonian Disorders / Postural Balance / Machine Learning / Models, Neurological Limits: Aged / Aged80 / Female / Humans / Male Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2021 Document type: Article Affiliation country: Francia Country of publication: Estados Unidos
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Accidental Falls / Parkinsonian Disorders / Postural Balance / Machine Learning / Models, Neurological Limits: Aged / Aged80 / Female / Humans / Male Language: En Journal: PLoS One Journal subject: CIENCIA / MEDICINA Year: 2021 Document type: Article Affiliation country: Francia Country of publication: Estados Unidos