Using machine learning-based analytics of daily activities to identify modifiable risk factors for falling in Parkinson's disease.

Panyakaew, Pattamon; Pornputtapong, Natapol; Bhidayasiri, Roongroj

Panyakaew, Pattamon; Pornputtapong, Natapol; Bhidayasiri, Roongroj.

Affiliation

Panyakaew P; Chulalongkorn Centre of Excellence for Parkinson's Disease & Related Disorders, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, 10330, Thailand.
Pornputtapong N; Department of Biochemistry and Microbiology, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand; Vaccine and Therapeutic Protein, the Special Task Force for Activating Research, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, 10330, Thailand.
Bhidayasiri R; Chulalongkorn Centre of Excellence for Parkinson's Disease & Related Disorders, Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, 10330, Thailand; The Academy of Science, The Royal Society of Thailand, Bangkok, 10330, Thailand. Electronic address: rbh@chulapd.org.

Parkinsonism Relat Disord ; 82: 77-83, 2021 01.

Article in En | MEDLINE | ID: mdl-33249293

Subject(s)

Accidental Falls; Activities of Daily Living; Parkinson Disease/diagnosis; Postural Balance; Risk Assessment; Supervised Machine Learning; Accidental Falls/statistics & numerical data; Age Factors; Aged; Antiparkinson Agents/therapeutic use; Female; Humans; Male; Middle Aged; Models, Theoretical; Parkinson Disease/drug therapy; Parkinson Disease/physiopathology; Postural Balance/physiology; Prognosis; Risk Assessment/methods; Risk Factors; Severity of Illness Index

Key words

Activities-specific balance confidence scale; Fall prediction; Fear of falling; Machine-learning; Parkinson's disease

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Parkinson Disease / Accidental Falls / Activities of Daily Living / Risk Assessment / Postural Balance / Supervised Machine Learning Type of study: Etiology_studies / Prognostic_studies / Risk_factors_studies Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Parkinsonism Relat Disord Journal subject: NEUROLOGIA Year: 2021 Document type: Article Affiliation country: Thailand Country of publication: United kingdom

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