Artificial intelligence is a growing phenomenon that is driving major changes to how we deliver healthcare. One of its most significant and challenging contributions is likely to be in diagnosis. Artificial intelligence is challenging the physician's exclusive role in diagnosis and in some areas, its diagnostic accuracy exceeds that of humans. We argue that we urgently need to consider how we will incorporate AI into our teaching of clinical reasoning in the undergraduate curriculum; students need to successfully navigate the benefits and potential issues of new and developing approaches to AI in clinical diagnosis. We offer a pedagogical framework for this challenging change to our curriculum.
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http://dx.doi.org/10.1080/0142159X.2019.1679361 | DOI Listing |
Sci Rep
January 2025
Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita City, Osaka, Japan.
Lymph node sampling with endoscopic ultrasound fine needle aspiration (EUS-FNA) may affect treatment options for biliary tract cancers. Our aim is to clarify its utility and clinical significance and the factors associated with FNA cytology positivity. Seventy-one consecutive patients with biliary tract cancer who underwent EUS-FNA to diagnose lymphadenopathies from April 2012 to July 2021 were enrolled retrospectively.
View Article and Find Full Text PDFOral Oncol
February 2025
Department of Nuclear Medicine, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou 510060, China. Electronic address:
Purpose: To investigate the prognostic value of post-chemoradiotherapy 2-[F]FDG PET/CT in locally advanced nasopharyngeal carcinoma (LANPC) and develop an accurate prognostic model based on the 2-[F]FDG PET/CT results.
Methods: 900 LANPC patients who underwent pretreatment and post-chemoradiotherapy 2-[F]FDG PET/CT from May 2014 to August 2022 were included in the study. We divided the patients into two distinct cohorts for the purpose of our study: a training cohort comprising 506 individuals, included from May 2008 to April 2020, and a validation cohort consisting of 394 individuals, included from May 2020 to August 2022.
Backgrounds: Biomedical research requires sophisticated understanding and reasoning across multiple specializations. While large language models (LLMs) show promise in scientific applications, their capability to safely and accurately support complex biomedical research remains uncertain.
Methods: We present , a novel question-and-answer benchmark for evaluating LLMs in biomedical research.
IEEE Trans Instrum Meas
May 2024
School of Mechanical Engineering, Shandong University, Jinan 250061, Shandong, China.
Automatic retinal layer segmentation with medical images, such as optical coherence tomography (OCT) images, serves as an important tool for diagnosing ophthalmic diseases. However, it is challenging to achieve accurate segmentation due to low contrast and blood flow noises presented in the images. In addition, the algorithm should be light-weight to be deployed for practical clinical applications.
View Article and Find Full Text PDFSudan J Paediatr
January 2024
Department of Medical Education, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Caring for critically ill children presents unique challenges due to their rapid deterioration and the need for immediate, complex interventions. The assessment, diagnosis and treatment of deteriorating paediatric patients require a comprehensive and holistic, systematic approach. However, the dynamic nature of critical illness and the need for stabilisation can often lead to missed opportunities for assessment and intervention.
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