Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1093/ced/llae258 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
CXR-LLaVA: a multimodal large language model for interpreting chest X-ray images.
Eur Radiol
January 2025
Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.
Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.
An unusual cause of hypertrophic cardiomyopathy in an infant: A case report and brief literature review.
Tunis Med
January 2025
University of Sfax, Military University Hospital of Sfax, Cardiology Department, Sfax, Tunisia.
Introduction: Nemaline myopathy (NM), also known as Nemalinosis, is a rare congenital muscle disease with an incidence of 1 in 50000. It is characterized by nemaline rods in muscle fibers, leading to muscle weakness. We reported a case of NM revealed by cardiac involvement, and we highlighted the challenges in diagnosing this condition as well as its poor prognosis.
View Article and Find Full Text PDFThe role of multi-modality imaging for the assessment of left atrium and left atrial appendage. A clinical consensus statement of the European Association of Cardiovascular Imaging (EACVI), European Heart Rhythm Association (EHRA) of the European Society of Cardiology (ESC).
Eur Heart J Cardiovasc Imaging
January 2025
Department of Cardiology, University of Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, Rennes, France.
Structural, architectural, contractile or electrophysiological alterations may occur in the left atrium (LA). The concept of LA cardiopathy is supported by accumulating scientific evidence demonstrating that LA remodeling has become a cornerstone diagnostic and prognostic marker. The structure and the function of LA and left atrial appendage (LAA) which is an integral part of the LA, are key elements for a better understanding of multiple clinical conditions, most notably atrial fibrillation (AF), cardioembolism, heart failure and mitral valve diseases.
View Article and Find Full Text PDFUsing the Regression Slope of Training Loss to Optimize Chest X-ray Generation in Deep Convolutional Generative Adversarial Networks.
Cureus
January 2025
Department of Critical Care Medicine, Jen Ho Hospital, Show Chwan Health Care System, Changhua, TWN.
Diffusion models, variational autoencoders, and generative adversarial networks (GANs) are three common types of generative artificial intelligence models for image generation. Among these, GANs are the most frequently used for medical image generation and are often employed for data augmentation in various studies. However, due to the adversarial nature of GANs, where the generator and discriminator compete against each other, the training process can sometimes end with the model unable to generate meaningful images or even producing noise.
View Article and Find Full Text PDFA Structured, Anatomy-Based Chest CT Interpretation Curriculum for Pulmonary Fellows Covering the Main Patterns of Parenchymal Lung Disease.
MedEdPORTAL
January 2025
Associate Professor, Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington School of Medicine; Staff Physician, Pulmonary, Critical Care and Sleep Medicine Section, Veterans Affairs Puget Sound Healthcare System.
Introduction: Chest computed tomography (CT) interpretation is a key competency for pulmonary fellows, with many resources intended for radiologists but very few for this specific group. We endeavored to create a curriculum to teach chest CT interpretation to first-year pulmonary fellows.
Methods: We assembled a team of two pulmonologists, one radiologist, and a fellow with computer drafting software experience.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!