BACKGROUND: Exposure of critically ill patients to antibiotics lead to intestinal dysbiosis, which often manifests as antibiotic-associated diarrhoea. Faecal microbiota transplantation restores gut microbiota and may lead to faster resolution of diar...
BACKGROUND AND OBJECTIVE: Randomized controlled trials (RCTs) are the cornerstone of evidence-based medicine. Unfortunately, not all RCTs are based on real data. This serious breach of research integrity compromises the reliability of systematic revi...
INTRODUCTION: As surgical accessibility improves, the incidence of postoperative complications is expected to rise. The implementation of a precise and objective risk stratification tool holds the potential to mitigate these complications by early id...
INTRODUCTION: Post-stroke movement disorders are common, especially upper limb dysfunction, which seriously affects the physical and mental health of stroke patients. With the continuous development of intelligent technology, robot-assisted therapy h...
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,...
Randomized controlled trials (RCTs) evaluating anti-cancer agents often lack generalizability to real-world oncology patients. Although restrictive eligibility criteria contribute to this issue, the role of selection bias related to prognostic risk r...
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...
BACKGROUND: The increasing development and spread of artificial and assistive intelligence is opening up new areas of application not only in applied medicine but also in related fields such as continuing medical education (CME), which is part of the...
International journal of surgery (London, England)
39903558
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...