Year: 2026
Type: article
Source: Medical Image Analysis
Authors: Ruining Deng, Tianyuan Yao, Yucheng Tang, Junlin Guo, Siqi Lu, Juming Xiong, Lining Yu, Quan Huu Cap, Pengzhou Cai, Libin Lan, Ze Zhao, Adrian Galdran, Amit Kumar, Gunjan Deotale, Dev Kumar Das, Inyoung Paik, Joonho Lee, Geongyu Lee, Yujia Chen, Wangkai Li, Zhaoyang Li, Xuege Hou, Zeyuan Wu, Shengjin Wang, Maximilian Fischer, Lars Krämer, Anghong Du, Le Zhang, Maria Sánchez Sánchez, Helena Sánchez Ulloa, David Ribalta Heredia, Carlos Pérez de Arenaza García, Shuoyu Xu, Bingdou He, Xinping Cheng, Tao Wang, Noémie Moreau, Katarzyna Bozek, Shubham Innani, Ujjwal Baid, Kaura Solomon Kefas, Bennett A. Landman, Yu Wang, Shilin Zhao, Mengmeng Yin, Haichun Yang, Yuankai Huo
Institutions: Vanderbilt University, Weill Cornell Medicine, Nvidia (United States), Chongqing Zhijian Life Technology Co., Ltd (China), Jinfeng Laboratory, Chongqing University of Technology, Chinese Academy of Sciences, Institute of Computing Technology, Universitat Pompeu Fabra, University of Science and Technology of China, Beijing National Research Center for Information Science and Technology, Tsinghua University, German Cancer Research Center, University of Birmingham, Nanjing University of Science and Technology, University of Cologne, Indiana University Indianapolis, Xi'an Jiaotong University, Vanderbilt University Medical Center
Language: English
Topic: AI in cancer detection
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, U.S. Department of Defense, Vanderbilt University, Leona M. and Harry B. Helmsley Charitable Trust, Nvidia, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, National Institute of Biomedical Imaging and Bioengineering
Awards: G1296419534, NSF Convergence Accelerator Track D: Scalable, TRaceable Ai for Imaging Translation: Innovation to Implementation for Accelerated Impact (STRAIT I3), G3514670832, G3870125724, G412688864, DEEP PHENOTYPING FSGS USING ARTIFICIAL INTELLIGENCE AND SPECIAL TRANSCRIPTOME, fMRI physiological signatures of aging and Alzheimer's Disease, G5235705212, G6573109839, G6665030671, Controlling Quality and Capturing Uncertainty in Advanced Diffusion Weighted MRI, G7623027640, CPS: Medium: iCMS: Intelligent Cyber Microscopy System for Long-term Microscope Imaging, AI-empowered 3D Computer Vision and Image-Omics Integration for Digital Kidney Histopathology, Dual-wavelength endoscopic Raman probe for eosinophilic esophagitis, Complementary ex vivo multimodal optical imaging and in vivo Raman spectroscopy to understand tissue dynamics
OpenAlex ID: W4407424705