Article

Alternative Prognosis of Recovery Assessment for the Hemiplegic Limb (APRAHL): a biomarker-free algorithm that predicts recovery potential for the hemiplegic upper-limb.

2022-05-09

Abstract excerpt

<h4>Objective: </h4> Stroke is a significant cause of disability, rendering patients with inability to perform activities of daily living due to lack of functional recovery. Precise prognosis in the early stage after stroke could enable realistic goal-setting and efficient resources allocation. Prediction algorithms have been tested and validate in the past, but they were using neurological biomarkers, thus they w...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 3a32a571-7ddd-596a-8cf4-0448390dd8ae
DOI: 10.21203/rs.3.rs-1163526/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Alternative Prognosis of Recovery Assessment for the Hemiplegic Limb (APRAHL): a biomarker-free algorithm that predicts recovery potential for the hemiplegic upper-limb.DOI 10.21203/rs.3.rs-1163526/v1Read

Sensor-Based Classification of Post-Stroke Motor Impairment Using Fugl-Meyer Lower Extremity ScoresSemantic proximity Read

Development and internal validation of a machine learning-based risk assessment model for prefrailty in hospitalized older patients with strokeSemantic proximity Read

Predictors and Prognostic Models for Early Discharge Planning of Hospitalized Acute Geriatric Patients, A Retrospective StudySemantic proximity Read

A novel clinical nomogram for predicting 3-month unfavorable outcomes of stroke patients treated with mechanical thrombectomySemantic proximity Read

iSPAN: Improved prediction of outcomes post thrombectomy with Machine LearningSemantic proximity Read

Enhancing Patient Rehabilitation Outcomes: Artificial Intelligence-Driven Predictive Modeling for Home Discharge in Neurological and Orthopedic ConditionsSemantic proximity Read

Guideline-Guided Prognostic Models of Mortality Following First-Ever Ischemic StrokeSemantic proximity Read

Real-time prospective (shadow mode) validation of an AI-based clinical decision support system for predicting 3-month functional outcome in acute stroke: the VALIDATE study protocolSemantic proximity Read

Development and internal validation of a machine learning–based prediction model and simplified screening score for in-hospital falls: a retrospective cohort studySemantic proximity Read

A Neutrophil-Incorporated Nomogram for Predicting 3-Month Disability after Intravenous Thrombolysis in Acute Ischemic StrokeSemantic proximity Read

Stroke-SCORE: Personalizing Acute Ischemic Stroke Treatment to Improve Patient OutcomesSemantic proximity Read

DISCO: A Delta-NIHSS-Based Machine Learning Model for Predicting Recurrence, Disability, and Mortality Following Acute Ischemic StrokeSemantic proximity Read