Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study

ML-based models effectively estimate fall risk across different clinical centers, enabling tailored interventions to enhance PD patients' quality of life. Challenges persist in predicting falls in US-based patients due to demographic and healthcare system differences.

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Publication Details

Journal
European Journal of Neurology
Published
2025-04-30
DOI
https://doi.org/10.1111/ene.70118
Citations
9
Primary Topic
Parkinson's Disease Mechanisms and Treatments
Type
article
Field-Weighted Citation Impact
12.50

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article

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study

Venet Osmani, Laura Avanzino, Bruno Giometto, Paola Mandich et al.
9 citations
European Journal of Neurology
Parkinson's Disease Mechanisms and Treatments
12.50
article

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study

Venet Osmani, Laura Avanzino, Bruno Giometto, Paola Mandich, Antonio Uccelli, Roberta Marchese, Monica Moroni, Stefano Bovo, Lorenzo Gios, Francesca Di Biasio, Flavio Ragni, Marco Chierici, Matteo Pardini, Manuela Marenco, Maria Chiara Malaguti, Chiara Longo, Giuseppe Jurman, Denise Cerne
article en
9 citations

Abstract

ML-based models effectively estimate fall risk across different clinical centers, enabling tailored interventions to enhance PD patients' quality of life. Challenges persist in predicting falls in US-based patients due to demographic and healthcare system differences.

European Journal of NeurologyVol. 32(5)
University of Trento (IT), Fondazione Bruno Kessler (IT), Associated Press (US), Provincia Autonoma di Trento (IT), Ospedale Policlinico San Martino (IT), University of Genoa (IT)
Ministero della Salute
Openalex Percentile: Top 1%
Parkinson's Disease Mechanisms and Treatments
12.50
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