Results 211 to 220 of about 10,079,567 (236)

Klotho‐Derived Peptide 1 Protects against Acute Kidney Injury by Directly Targeting Mitochondrial ATAD3A

Advanced Science, EarlyView.
This study uncovers that KP1, a Klotho‐derived peptide, protects the kidney against acute kidney injury, a clinical syndrome with high morbidity and mortality. KP1 enters tubular epithelial cells via endocytosis, directly interacts with the mitochondrial ATAD3A/HIGD2A complex, thereby preventing cytochrome c release, and caspases activation, and ...
Xiaoyao Zhang, Shihui Lin, Tianyu Wu, Zhixin Zhang, Hong Zhou, Xue Hong, Youhua Liu   +6 more
wiley   +1 more source

CanLRHI: a multimodal pretraining model for cell death analysis in cancer pathology based on long-text representation and high-resolution images. [PDF]

Brief Bioinform
Zhang T, Wan L, Zhang H, Zhao Z, Cui H, Ma J.   +5 more
europepmc   +1 more source

SurgViVQA: temporally grounded video question answering for surgical scene understanding. [PDF]

Int J Comput Assist Radiol Surg
Drago MO, Carlini L, Balyemez PC, Pierantozzi D, Lena C, Hassan C, Stoyanov D, Momi E, Bano S, Hoque MI.   +9 more
europepmc   +1 more source

A data-efficient 3D medical vision-language model using only a 2D encoder. [PDF]

Sci Rep
Lian Y, Xie Y, Jiang Y, Wang L, Yu H.
europepmc   +1 more source

Accuracy, Self-Reported Confidence, and Overconfidence of Large Language Models in Endodontics: An Evaluation Using National Specialty Examination Questions. [PDF]

Med Sci Monit
Adıgüzel M.
europepmc   +1 more source

Physics-Informed Neural Networks Meet Multimodal Large Language Models: Biomechanical Simulation in Aortic Aneurysm. [PDF]

Cyborg Bionic Syst
Zhu S, Abudupataer M, Wang Y, Zhang H, Lai H, Zhu K, Sun Y, Chen N.   +7 more
europepmc   +1 more source

BEnchmarking Large Language Models for Ophthalmology (BELO): An Expert-Curated Data Set and Evaluation Framework for Knowledge and Reasoning. [PDF]

Ophthalmol Sci
Srinivasan S, Ai X, Lo TWS, Gilson A, Zou M, Zou K, Kim H, Yang M, Pushpanathan K, Yew SME, Loke WT, Goh JHL, Chen Y, Kong Y, Fu EY, Ong M, Nwanyanwu K, Dave A, Li KZ, Sun CH, Chia M, Yang GD, Wong WM, Chen DZ, Liu D, Singer M, Antaki F, Del Priore LV, Jonas JB, Adelman R, Chen Q, Tham YC.   +31 more
europepmc   +1 more source

Medical visual question answering: A survey [PDF]

Artificial Intelligence in Medicine, 2023
Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. Given a medical image and a clinically relevant question in natural language, the medical VQA system is expected to predict a ...
Gholamreza Haffari, Zongyuan Ge, Mingguang He   +2 more
exaly   +2 more sources

A Question-Centric Model for Visual Question Answering in Medical Imaging [PDF]

IEEE Transactions on Medical Imaging, 2020
Deep learning methods have proven extremely effective at performing a variety of medical image analysis tasks. With their potential use in clinical routine, their lack of transparency has however been one of their few weak points, raising concerns ...
Raphael Sznitman, Tommy Löfstedt, Minh Vu   +2 more
exaly   +3 more sources