Clinical event extraction is crucial for structuring medical data, supporting clinical decision-making, and enabling other intelligent healthcare services. Traditional approaches for clinical event extraction often use pipeline-based methods to ident...
BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. Existing risk scores and criteria for paediatric sepsis are not well-suited for early diagnosis in ED...
BACKGROUND: This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, partic...
Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
May 13, 2025
OBJECTIVES: To analyze agreement between diagnoses issued by the Mediktor application and those of an attending physician, and to evaluate the usefulness of this application in patients who seek emergency care.
Current neurology and neuroscience reports
May 9, 2025
PURPOSE OF REVIEW: Artificial intelligence (AI) promises to compress stroke treatment timelines, yet its clinical return on investment remains uncertain. We interrogate state‑of‑the‑art AI platforms across imaging, workflow orchestration, and outcome...
The study by Huang , published in the , advances intrahepatic cholangiocarcinoma (ICC) management by developing a machine-learning model to predict textbook outcomes (TO) based on preoperative factors. By analyzing data from 376 patients across four ...
The study by Huang , published in the , advances intrahepatic cholangiocarcinoma (ICC) management by developing a machine-learning model to predict textbook outcomes (TO) based on preoperative factors. By analyzing data from 376 patients across four ...
BACKGROUND: The objective of this study was to evaluate the concordance between therapeutic recommendations proposed by a multidisciplinary team meeting and those generated by a large language model (ChatGPT) for colorectal cancer. Although multidisc...
Generative Pre-trained Transformer (GPT)-4, a versatile conversational artificial intelligence, has potential applications in medicine, but its ability to support physicians' decision-making remains unclear. We evaluated GPT-4's performance in assist...
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang , which presents a recent multicenter cohort study demonstrated that machine learning algorithms effectively strati...
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