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Atypical Left Ventricular Remodeling in Fabry Cardiomyopathy: The Key Diagnostic Role of T1 Mapping.
Circ Cardiovasc Imaging
January 2025
Multimodality Cardiac Imaging Section, IRCCS Policlinico San Donato, Milan, Italy (L.T., G.D., M.L., A.C.).
Reading comics: The effect of expertise on eye movements.
J Eye Mov Res
November 2024
School of Literature and Journalism Sichuan University, China.
The theory of expertise suggests that there should be observable differences in the eye movement patterns between experts and non-experts. Previous studies have investigated how expertise influences eye movement patterns during cognitive tasks like reading. However, the impact of expertise on eye movements in comics, a multimodal form of text, remains unexplored.
View Article and Find Full Text PDFNoncoding variants and sulcal patterns in congenital heart disease: Machine learning to predict functional impact.
iScience
February 2025
Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA.
Neurodevelopmental impairments associated with congenital heart disease (CHD) may arise from perturbations in brain developmental pathways, including the formation of sulcal patterns. While genetic factors contribute to sulcal features, the association of noncoding variants (ncDNVs) with sulcal patterns in people with CHD remains poorly understood. Leveraging deep learning models, we examined the predicted impact of ncDNVs on gene regulatory signals.
View Article and Find Full Text PDFMulti-modality imaging features of cavernous haemangioma of the right ventricle.
Eur Heart J Case Rep
January 2025
Department of MRI, Wuhan Asia General Hospital, Wuhan 430050, China.
Glaucoma Detection and Feature Identification via GPT-4V Fundus Image Analysis.
Ophthalmol Sci
November 2024
Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology, Shiley Eye Institute, University of California, San Diego, La Jolla, California.
Purpose: The aim is to assess GPT-4V's (OpenAI) diagnostic accuracy and its capability to identify glaucoma-related features compared to expert evaluations.
Design: Evaluation of multimodal large language models for reviewing fundus images in glaucoma.
Subjects: A total of 300 fundus images from 3 public datasets (ACRIMA, ORIGA, and RIM-One v3) that included 139 glaucomatous and 161 nonglaucomatous cases were analyzed.
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