Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Machine learning methods for functional recovery prediction and prognosis in post-stroke rehabilitation: a systematic review
102
Zitationen
6
Autoren
2022
Jahr
Abstract
We identified several methodological limitations: small sample sizes, a limited number of external validation approaches, and high heterogeneity among input and output variables. Although these elements prevented a quantitative comparison across models, we defined the most frequently used models given a specific outcome, providing useful indications for the application of more complex machine learning algorithms in rehabilitation medicine.
Ähnliche Arbeiten
The Timed “Up & Go”: A Test of Basic Functional Mobility for Frail Elderly Persons
1991 · 14.034 Zit.
Guidelines for the Early Management of Patients With Acute Ischemic Stroke: 2019 Update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association/American Stroke Association
2019 · 6.961 Zit.
Thrombolysis with Alteplase 3 to 4.5 Hours after Acute Ischemic Stroke
2008 · 6.552 Zit.
A Randomized Trial of Intraarterial Treatment for Acute Ischemic Stroke
2014 · 6.504 Zit.
Measurements of acute cerebral infarction: a clinical examination scale.
1989 · 5.745 Zit.