BACKGROUND: Robotic rehabilitation, which provides a high-intensity, high-frequency therapy to improve neuroplasticity, is gaining traction. However, its effectiveness for upper extremity stroke rehabilitation remains uncertain. This study comprehens...
OBJECTIVES: Adherence to established reporting guidelines can improve clinical trial reporting standards, but attempts to improve adherence have produced mixed results. This exploratory study aimed to determine how accurate a large language model gen...
BACKGROUND: The application of intelligent robots in therapy is becoming more and more important for people with dementia. More extensive research is still needed to evaluate its impact on behavioral and psychological dementia symptoms, as well as qu...
Predictive biomarker identification in cancer treatment has traditionally relied on pre-defined analyses, limiting discoveries to expected biomarkers and potentially overlooking novel ones predictive of therapy response. In this work, we develop a no...
INTRODUCTION: Combining repetitive transcranial magnetic stimulation (rTMS) with robotic training could result in more significant improvements in motor function than either treatment alone. The efficacy of this combination may depend on the sequenci...
International journal of surgery (London, England)
Mar 1, 2025
The advancement of large language models (LLMs) presents promising opportunities to enhance evidence synthesis efficiency, particularly in data extraction processes, yet existing prompts for data extraction remain limited, focusing primarily on commo...
INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demon...
BACKGROUND: Classical approaches to subgroup analysis in randomised controlled trials (RCTs) to identify heterogeneous treatment effects (HTEs) involve testing the interaction between each pre-specified possible treatment effect modifier and the trea...
Recent advancements in machine learning (ML) for analyzing heterogeneous treatment effects (HTE) are gaining prominence within the medical and epidemiological communities, offering potential breakthroughs in the realm of precision medicine by enablin...
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