AI Medical Compendium Topic

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Randomized Controlled Trials as Topic

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Automated confidence ranked classification of randomized controlled trial articles: an aid to evidence-based medicine.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: For many literature review tasks, including systematic review (SR) and other aspects of evidence-based medicine, it is important to know whether an article describes a randomized controlled trial (RCT). Current manual annotation is not com...

"You gotta try it all": Parents' Experiences with Robotic Gait Training for their Children with Cerebral Palsy.

Physical & occupational therapy in pediatrics
AIMS: Innovative robotic technologies hold strong promise for improving walking abilities of children with cerebral palsy (CP), but may create expectations for parents pursuing the "newest thing" in treatment. The aim of this qualitative study was to...

Using Machine Learning to Predict Uptake to an Online Self-Guided Intervention for Stress During the COVID-19 Pandemic.

Stress and health : journal of the International Society for the Investigation of Stress
Online self-guided interventions appear efficacious for alleviating some mental health concerns. However, among persons who are offered online interventions, only a fraction access them (i.e., achieve uptake). Machine learning methods may be useful t...

Deep learning for electrocardiogram interpretation: Bench to bedside.

European journal of clinical investigation
BACKGROUND: Recent advancements in deep learning (DL), a subset of artificial intelligence, have shown the potential to automate and improve disease recognition, phenotyping and prediction of disease onset and outcomes by analysing various sources of...

Predicting Postoperative Circulatory Complications in Older Patients: A Machine Learning Approach.

Biomedical and environmental sciences : BES
OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients.

Comparison of Different Machine Learning Methodologies for Predicting the Non-Specific Treatment Response in Placebo Controlled Major Depressive Disorder Clinical Trials.

Clinical and translational science
Placebo effect represents a serious confounder for the assessment of treatment effect to the extent that it has become increasingly difficult to develop antidepressant medications appropriate for outperforming placebo. Treatment effect in randomized,...

The 'golden fleece of embryology' eludes us once again: a recent RCT using artificial intelligence reveals again that blastocyst morphology remains the standard to beat.

Human reproduction (Oxford, England)
Grading of blastocyst morphology is used routinely for embryo selection with good outcomes. A lot of effort has been placed in IVF to search for the prize of selecting the most viable embryo to transfer ('the golden fleece of embryology'). To improve...

Artificial Intelligence in Cardiovascular Clinical Trials.

Journal of the American College of Cardiology
Randomized clinical trials are the gold standard for establishing the efficacy and safety of cardiovascular therapies. However, current pivotal trials are expensive, lengthy, and insufficiently diverse. Emerging artificial intelligence (AI) technolog...

Randomised controlled trials evaluating artificial intelligence in clinical practice: a scoping review.

The Lancet. Digital health
This scoping review of randomised controlled trials on artificial intelligence (AI) in clinical practice reveals an expanding interest in AI across clinical specialties and locations. The USA and China are leading in the number of trials, with a focu...

Effects of robot-assisted gait training on motor performance of lower limb in poststroke survivors: a systematic review with meta-analysis.

European review for medical and pharmacological sciences
OBJECTIVE: This study aimed to investigate the effects of robot-assisted gait training (RAGT) on improving walking ability, and to determine the optimal dosage of task-specific training based on RAGT for stroke patients.