AIMC Topic: Outcome Assessment, Health Care

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Modeling and measurement of signaling outcomes affecting decision making in noisy intracellular networks using machine learning methods.

Integrative biology : quantitative biosciences from nano to macro
Characterization of decision-making in cells in response to received signals is of importance for understanding how cell fate is determined. The problem becomes multi-faceted and complex when we consider cellular heterogeneity and dynamics of biochem...

Postimplementation Evaluation of a Machine Learning-Based Deterioration Risk Alert to Enhance Sepsis Outcome Improvements.

Nursing administration quarterly
Machine learning-based early warning systems (EWSs) can detect clinical deterioration more accurately than point-score tools. In patients with sepsis, however, the timing and scope of sepsis interventions relative to an advanced EWS alert are not wel...

An outcome model approach to transporting a randomized controlled trial results to a target population.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the tar...

The Role of the ACR Data Science Institute in Advancing Health Equity in Radiology.

Journal of the American College of Radiology : JACR
Commercially available artificial intelligence (AI) algorithms outside of health care have been shown to be susceptible to ethnic, gender, and social bias, which has important implications in the development of AI algorithms in health care and the ra...

Improvement of motor performance in children with cerebral palsy treated with exoskeleton robotic training: A retrospective explorative analysis.

Restorative neurology and neuroscience
BACKGROUND: Robot-assisted gait training (RAGT) is widely used in children with cerebral palsy (CP), but information about optimal intervention frequency and duration is still lacking and the current evidence about effect of RAGT on motor endurance a...

Effectiveness of robot-assisted gait training on motor impairments in people with Parkinson's disease: a systematic review and meta-analysis.

International journal of rehabilitation research. Internationale Zeitschrift fur Rehabilitationsforschung. Revue internationale de recherches de readaptation
The aim of this systematic review and meta-analysis was to evaluate the effectiveness of robot-assisted gait training (RAGT) on motor impairments in people with Parkinson's disease (PD). A computer-based systematic literature search was performed in ...

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Schizophrenia bulletin
BACKGROUND: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' r...

Gait training with Hybrid Assistive Limb enhances the gait functions in subacute stroke patients: A pilot study.

NeuroRehabilitation
BACKGROUND: The robotic Hybrid Assistive Limb (HAL) provides motion according to the wearer's voluntary activity. HAL training effects on walking speed and capacity have not been clarified in subacute stroke.

A Case Study of the Impact of Data-Adaptive Versus Model-Based Estimation of the Propensity Scores on Causal Inferences from Three Inverse Probability Weighting Estimators.

The international journal of biostatistics
OBJECTIVE: Consistent estimation of causal effects with inverse probability weighting estimators is known to rely on consistent estimation of propensity scores. To alleviate the bias expected from incorrect model specification for these nuisance para...