AIMC Topic: Randomized Controlled Trials as Topic

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Early efficacy observation of suspended lower-limb rehabilitation robot-assisted therapy in patients with intensive care unit-acquired weakness: a study protocol for a self-controlled randomised controlled trial.

BMJ open
INTRODUCTION: Intensive care unit-acquired weakness (ICUAW) is a common and severe complication in critically ill patients, associated with high morbidity and poor prognosis. Despite increasing focus on ICUAW, definitive diagnostic and therapeutic st...

Coronary Computed Tomographic Angiography to Optimize the Diagnostic Yield of Invasive Angiography for Low-Risk Patients Screened With Artificial Intelligence: Protocol for the CarDIA-AI Randomized Controlled Trial.

JMIR research protocols
BACKGROUND: Invasive coronary angiography (ICA) is the gold standard in the diagnosis of coronary artery disease (CAD). Being invasive, it carries rare but serious risks including myocardial infarction, stroke, major bleeding, and death. A large prop...

Effectiveness of AI-Driven Conversational Agents in Improving Mental Health Among Young People: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: The increasing prevalence of mental health issues among adolescents and young adults, coupled with barriers to accessing traditional therapy, has led to growing interest in artificial intelligence (AI)-driven conversational agents (CAs) a...

Electromechanical-assisted training for walking after stroke.

The Cochrane database of systematic reviews
RATIONALE: Walking difficulties are common after a stroke. During rehabilitation, electromechanical and robotic gait-training devices can help improve walking. As the evidence and certainty of the evidence may have changed since our last update in 20...

Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: As the optimal treatment for end-stage renal disease, kidney transplantation has proven instrumental in enhancing patient survival and quality of life. Suboptimal medication adherence is recognized as an independent risk factor for poor p...

Transformer-Based Language Models for Group Randomized Trial Classification in Biomedical Literature: Model Development and Validation.

JMIR medical informatics
BACKGROUND: For the public health community, monitoring recently published articles is crucial for staying informed about the latest research developments. However, identifying publications about studies with specific research designs from the extens...

Concordance with SPIRIT-AI guidelines in reporting of randomized controlled trial protocols investigating artificial intelligence in oncology: a systematic review.

The oncologist
BACKGROUND: Artificial intelligence (AI) is a promising tool used in oncology that may be able to facilitate diagnosis, treatment planning, and patient management. Transparency and completeness of protocols of randomized controlled trials (RCT) invol...

Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.

Journal of hepatology
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...

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...