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Evidence-Based Medicine

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Evidence-Based Learning Strategies in Medicine Using AI.

JMIR medical education
Large language models (LLMs), like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of examination questions, and streamlin...

Navigating the uncommon: challenges in applying evidence-based medicine to rare diseases and the prospects of artificial intelligence solutions.

Medicine, health care, and philosophy
The study of rare diseases has long been an area of challenge for medical researchers, with agonizingly slow movement towards improved understanding of pathophysiology and treatments compared with more common illnesses. The push towards evidence-base...

Why your doctor is not an algorithm: Exploring logical principles of different clinical inference methods using liver transplantation as a model.

Gastroenterologia y hepatologia
The development of machine learning (ML) tools in many different medical settings is largely increasing. However, the use of the resulting algorithms in daily medical practice is still an unsolved challenge. We propose an epistemological approach (i....

Machine learning to optimize literature screening in medical guideline development.

Systematic reviews
OBJECTIVES: In a time of exponential growth of new evidence supporting clinical decision-making, combined with a labor-intensive process of selecting this evidence, methods are needed to speed up current processes to keep medical guidelines up-to-dat...

Towards Autonomous Living Meta-Analyses: A Framework for Automation of Systematic Review and Meta-Analyses.

Studies in health technology and informatics
Systematic review and meta-analysis constitute a staple of evidence-based medicine, an obligatory step in developing the guideline and recommendation document. It is a formalized process aiming at extracting and summarizing knowledge from the publish...

Clinical Evaluation of Artificial Intelligence-Enabled Interventions.

Investigative ophthalmology & visual science
Artificial intelligence (AI) health technologies are increasingly available for use in real-world care. This emerging opportunity is accompanied by a need for decision makers and practitioners across healthcare systems to evaluate the safety and effe...

Explanatory argument extraction of correct answers in resident medical exams.

Artificial intelligence in medicine
Developing technology to assist medical experts in their everyday decision-making is currently a hot topic in the field of Artificial Intelligence (AI). This is specially true within the framework of Evidence-Based Medicine (EBM), where the aim is to...

Benchmarking Human-AI collaboration for common evidence appraisal tools.

Journal of clinical epidemiology
BACKGROUND AND OBJECTIVE: It is unknown whether large language models (LLMs) may facilitate time- and resource-intensive text-related processes in evidence appraisal. The objective was to quantify the agreement of LLMs with human consensus in apprais...

Is Artificial Intelligence (AI) currently able to provide evidence-based scientific responses on methods that can improve the outcomes of embryo transfers? No.

JBRA assisted reproduction
OBJECTIVE: The rapid development of Artificial Intelligence (AI) has raised questions about its potential uses in different sectors of everyday life. Specifically in medicine, the question arose whether chatbots could be used as tools for clinical de...

Aceso-DSAL: Discovering Clinical Evidences From Medical Literature Based on Distant Supervision and Active Learning.

IEEE journal of biomedical and health informatics
Automatic extraction of valuable, structured evidence from the exponentially growing clinical trial literature can help physicians practice evidence-based medicine quickly and accurately. However, current research on evidence extraction has been limi...