Computer-aided #colonoscopy (CAC) may improve polyp detection and characterization compared to traditional colonoscopy (TC). However, recent studies also reported no relevant effect on #adenoma detection rate (ADR). This study evaluates the real-time #polyp detection system EndoMind during screening and surveillance colonoscopy in a multicenter randomized controlled trial. From November 2021 to November 2022, 933 individuals… Continue reading Artificial intelligence assisted colorectal lesion detection in private practices a randomized controlled study
Tag: artificial-intelligence
The Role of Artificial Intelligence in Diagnosing Pulmonary Embolism: A Systematic Review and Meta-analysis
Introduction: Missed or delayed diagnosis of pulmonary embolism (#PE ) is associated with increased morbidity, mortality, and longer hospitalizations. This study aimed to evaluate the diagnostic accuracy of Artificial Intelligence (#AI ) models in detecting PE across imaging.Methods: We systematically searched PubMed/MEDLINE, Scopus, Embase and Web of Science from inception to 1 January 2025 without… Continue reading The Role of Artificial Intelligence in Diagnosing Pulmonary Embolism: A Systematic Review and Meta-analysis
How to predict abnormal acid reflux: recent developments
IntroductionRecent advances in physiology and technology have led to the identification of additional parameters that have the potential to enhance diagnostic accuracy and inform the management of Gastroesophageal reflux disease ( #GERD ). Whilst traditional pH monitoring and acid exposure time (AET) remain central to diagnosis, recent advances have introduced novel physiological markers that improve… Continue reading How to predict abnormal acid reflux: recent developments
Beyond human gold standards: A multimodel framework for automated abstract classification and information extraction
Meta-research and evidence synthesis require considerable resources. Large language models (#LLMs ) have emerged as promising tools to assist in these processes, yet their performance varies across models, limiting their reliability. Taking advantage of the large availability of small size (<10 billion parameters) open-source LLMs, we implemented an agreement-based framework in which a decision is… Continue reading Beyond human gold standards: A multimodel framework for automated abstract classification and information extraction
Human-large language model collaboration in clinical medicine: a systematic review and meta-analysis
Human- #AI collaboration (H + AI) using large language models ( #LLMs ) offers a promising approach to enhance clinical reasoning, documentation, and interpretation tasks. Following PRISMA 2020 (PROSPERO registration: CRD420251068272), we systematically compared H + AI with human-only (H) workflows, searching four databases through June 28, 2025. Ten peer-reviewed studies met eligibility criteria, with… Continue reading Human-large language model collaboration in clinical medicine: a systematic review and meta-analysis
Effective prompt design for large language models in clinical #practice
Large language models ( #LLMs ) have emerged as transformative healthcare tools for clinical documentation, diagnostic reasoning, and medical education. However, effective utilization requires understanding prompt engineering principles—the strategic design of inputs to optimize performance while mitigating hallucination, bias, and outdated information.MethodsThis narrative review synthesizes evidence from a structured PubMed search through December 2025 using… Continue reading Effective prompt design for large language models in clinical #practice
Comparison of verbal autopsy using a large #language model to biologically confirmed causes of death for #malaria and other communicable diseases among children in six sub-Saharan African countries
Malaria, a preventable parasitic disease, causes most child deaths in sub-Saharan Africa (SSA). Reliable cause-of-death data are essential to evaluate progress toward the national and global malaria control goals. However, civil registration and vital statistics are often weak and incomplete in many low- and middle-income countries. In such circumstances, verbal autopsy (VA) provides an alternative… Continue reading Comparison of verbal autopsy using a large #language model to biologically confirmed causes of death for #malaria and other communicable diseases among children in six sub-Saharan African countries
AI in Hand #Surgery: Assessing Large Language Models in the Classification and Management of #Hand Injuries
AbstractBackground: OpenAI's ChatGPT (San Francisco, CA, USA) and Google's Gemini (Mountain View, CA, USA) are two large language models that show promise in improving and expediting medical decision making in hand surgery. Evaluating the applications of these models within the field of hand surgery is warranted. This study aims to evaluate ChatGPT-4 and Gemini in… Continue reading AI in Hand #Surgery: Assessing Large Language Models in the Classification and Management of #Hand Injuries
The Future of #Artificial #Intelligence in Medical Education and Continuing #Medical Education
In this article, we explore the transformative potential of artificial intelligence (AI) in medical education and continuing medical education. We discuss the rapid evolution of AI technology, particularly generative AI and large language models, and their implications for teaching and learning. We emphasize the importance of AI literacy, ethical considerations, and evidence-based approaches to integrating… Continue reading The Future of #Artificial #Intelligence in Medical Education and Continuing #Medical Education
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