AIMC Topic: Outcome Assessment, Health Care
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Effectiveness of robot-assisted training in adults with Parkinson's disease: a systematic review and meta-analysis.
Journal of neurology
Dec 12, 2024
AIM: This work aimed to update and summarize the existing evidence on the effectiveness of robot-assisted training (RAT) in adults with Parkinson's disease (PD).
Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.
Journal of psychiatric research
Dec 4, 2024
Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population...
Area Under Curve
Outcome Assessment, Health Care
Veterans
Outpatients
ROC Curve
United States
Treatment Outcome
Mental Health Services
Patient Health Questionnaire
Young Adult
Adult
Male
Middle Aged
Depression
Latent Class Analysis
Adolescent
Stress Disorders, Post-Traumatic
Female
Reproducibility of Results
Aged
Aged, 80 and over
Humans
Machine Learning
Retrospective Studies
Prediction of pharmacological response in OCD using machine learning techniques and clinical and neuropsychological variables.
Spanish journal of psychiatry and mental health
Nov 15, 2024
INTRODUCTION: Obsessive compulsive disorder is associated with affected executive functioning, including memory, cognitive flexibility, and organizational strategies. As it was reported in previous studies, patients with preserved executive functions...
Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology.
La Radiologia medica
Sep 3, 2024
Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and measures are employed in the clinical evaluation of AI, presenting a ...
Machine learning models for outcome prediction in thrombectomy for large anterior vessel occlusion.
Annals of clinical and translational neurology
Aug 23, 2024
OBJECTIVE: Predicting long-term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to d...
Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction.
Neurocritical care
Aug 13, 2024
BACKGROUND: The prognostication of long-term functional outcomes remains challenging in patients with traumatic brain injury (TBI). Our aim was to demonstrate that intensive care unit (ICU) variables are not efficient to predict 6-month functional ou...
Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.
Neurocritical care
Aug 6, 2024
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.
Outcome risk model development for heterogeneity of treatment effect analyses: a comparison of non-parametric machine learning methods and semi-parametric statistical methods.
BMC medical research methodology
Jul 23, 2024
BACKGROUND: In randomized clinical trials, treatment effects may vary, and this possibility is referred to as heterogeneity of treatment effect (HTE). One way to quantify HTE is to partition participants into subgroups based on individual's risk of e...
Surface electromyography vs clinical outcome measures after robot-assisted gait training in patients with spinal cord injury after post-acute phase of rehabilitation.
Annals of agricultural and environmental medicine : AAEM
Jul 8, 2024
INTRODUCTION AND OBJECTIVE: Surface electromyography (sEMG) measurements are a valid method for sublesional muscle activity following spinal cord injury (SCI). In the literature there are few reports evaluating the effect of robotic assisted gait tra...
Study of machine learning techniques for outcome assessment of leptospirosis patients.
Scientific reports
Jun 17, 2024
Leptospirosis is a global disease that impacts people worldwide, particularly in humid and tropical regions, and is associated with significant socio-economic deficiencies. Its symptoms are often confused with other syndromes, which can compromise cl...
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