AI Medical Compendium Topic

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Randomized Controlled Trials as Topic

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Effects of proximal priority and distal priority robotic priming techniques with impairment-oriented training of upper limb functions in patients with chronic stroke: study protocol for a single-blind, randomized controlled trial.

Trials
BACKGROUND: The sequence of establishing a proximal stability or function before facilitation of the distal body part has long been recognized in stroke rehabilitation practice but lacks scientific evidence. This study plans to examine the effects of...

Creating efficiencies in the extraction of data from randomized trials: a prospective evaluation of a machine learning and text mining tool.

BMC medical research methodology
BACKGROUND: Machine learning tools that semi-automate data extraction may create efficiencies in systematic review production. We evaluated a machine learning and text mining tool's ability to (a) automatically extract data elements from randomized t...

Robot-assisted gait training in individuals with spinal cord injury: A systematic review for the clinical effectiveness of Lokomat.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: Spinal cord injury (SCI) is a critical medical condition that causes numerous impairments leading to accompanying disability. Robotic-assisted gait training (RAGT) offers many advantages, including the capability to increase the intensity...

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.

Annals of epidemiology
Purpose Machine learning is an attractive tool for identifying heterogeneous treatment effects (HTE) of interventions but generalizability of machine learning derived HTE remains unclear. We examined generalizability of HTE detected using causal fore...

A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but is limited by variability in interpretation and insensitivity to change. Thus, there is a critical n...

Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

Randomised controlled trials in medical AI: ethical considerations.

Journal of medical ethics
In recent years, there has been a surge of high-profile publications on applications of artificial intelligence (AI) systems for medical diagnosis and prognosis. While AI provides various opportunities for medical practice, there is an emerging conse...

Role of Artificial Intelligence Applications in Real-Life Clinical Practice: Systematic Review.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) applications are growing at an unprecedented pace in health care, including disease diagnosis, triage or screening, risk analysis, surgical operations, and so forth. Despite a great deal of research in the dev...

Are social robots ready yet to be used in care and therapy of autism spectrum disorder: A systematic review of randomized controlled trials.

Neuroscience and biobehavioral reviews
Autism is a neurodevelopmental disorder that affects the everyday life of people who have this lifelong condition. Robots hold great promise for uplifting therapy and care of the affected population. We searched Scopus, Medline, ScienceDirect, Web of...

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data.

Nature communications
Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features ...