Results 161 to 170 of about 89,843 (211)

Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network. [PDF]

IEEE Trans Med Imaging, 2019
Xiong Z, Fedorov VV, Fu X, Cheng E, Macleod R, Zhao J.   +5 more
europepmc   +1 more source

A Bio‐Inspired Visual Sensor With UV‐to‐NIR Fusion for Enhanced Recognition in Autonomous Driving Systems

Advanced Science, EarlyView.
Inspired by the sophisticated multilayer retinal architecture found in Pacific salmon eyes, a novel van der Waals heterojunction sensor based on NbNiTe5/BP is designed. Upon illumination at distinct wavelengths of 365 and 820 nm, the device exhibits distinctive bipolar photocurrent responses with opposite polarities. This unique optoelectronic behavior
Tianle Zeng, Zishen Zhao, Keqin Tang, Yawen Luo, Junxin Yan, Kun Ye, Jinlu Liu, Zhuo Dong, Zhipeng Yu, Weiming Lv, Ruicheng Li, Yenasheng Li, Lixuan Liu, Tianyu Xue, Chun Zhao, Yan Zhou, Kai Zhang, Zhongming Zeng, Zhongyuan Liu   +18 more
wiley   +1 more source

Disentangling Heterogeneous Molecular Networks for Multi‐Omics‐Driven Cancer Driver Discovery

Advanced Science, EarlyView.
DRIVE integrates PPI topology and pan‐cancer multi‐omics profiles through dual‐view graph disentanglement, contrastive representation learning, and joint optimization. Across six PPI networks, DRIVE outperforms ten baselines and remains robust to structural and annotation perturbations.
Xinjing Gong, Ji Li, Mu Su, Peishen Yu, Te Ma, Ruiyang Zhai, Chenye Zhang, Mengyan Zhang, Yan Zhang   +8 more
wiley   +1 more source

qcGEM: A Graph‐Based Molecular Representation With Quantum Chemistry Awareness

Advanced Science, EarlyView.
In this work, we introduce qcGEM, a quantum‐chemistry‐aware graph‐based embedding of molecules that incorporates physical priors into molecular representation learning. Through a specially designed model architecture to adequately process quantum chemistry information as well as three‐dimensional molecular geometry, qcGEM provides a compact, physics ...
Haoyu Wang, Ziyan Zhang, Swee Hong Ng, Haipeng Gong   +3 more
wiley   +1 more source

PrOMet: Accurate and Robust Metal‐Binding Site and Type Prediction

Advanced Science, EarlyView.
PrOMet is a two‐stage deep learning framework for jointly predicting metal‐binding sites and ion identities from protein structures. Surface candidate sites are first pruned, followed by refinement of the most probable sites and metal types. This hierarchical strategy enables robust and accurate metal prediction for cryo‐EM and AlphaFold‐derived ...
Gangeun Park, Chaok Seok, Hahnbeom Park
wiley   +1 more source

Transformer‐Based Multitask Framework Integrating Habitat and Deep Learning for Predicting Early Disease Control and Survival in Immunotherapy‐Treated Hepatocellular Carcinoma

Advanced Science, EarlyView.
This study developed ECOS‐Net, a transformer‐based multitask framework integrating CT‐derived habitat and 2.5D deep learning features to simultaneously predict early disease control and overall survival in hepatocellular carcinoma patients treated with immune checkpoint inhibitors.
Xiaona Fu, Yusheng Guo, Bingxin Gong, Jie Lou, Ning Wang, Xuejun Chen, Hongtao Hu, Rundong Wang, Xiaofang Guo, Shanmei Li, Yangyang Xie, Shichao Long, Mengsi Li, Shubo Pan, Wen Shen, Zhaogang Zhang, Zifang Song, Pengchen Liang, Xiaoyun Liang, Peng Sun, Guilin Zhang, Shanshan Jiang, Jinxiang Zhang, Lian Yang   +23 more
wiley   +1 more source

An Integrated Artificial Intelligence Framework for Nanomedicine Engineering

Advanced Science, EarlyView.
This review outlines a closed‐loop AI ecosystem for nanomedicine engineering. By synergizing multimodal data harmonization, objective‐driven AI architectures, and automated high‐throughput validation, this “Design‐Make‐Test‐Analyze” (DMTA) workflow transforms traditional heuristic formulation into a predictive, self‐optimizing paradigm, accelerating ...
Meichen Dong, Qin Luo, Xinyi Ding, Chaoqi Lu, Ru Zhang, Qingqing Tan, Zhiqing Pang, Defang Ouyang, Dongsheng Li, Jiaxuan Xia, Jianxin Wang   +10 more
wiley   +1 more source

Enhancing Specific Stiffness of Nano‐Architected Materials Through Generative AI and Active Learning

Advanced Science, EarlyView.
A structure‐centric generative framework searches voxelated design space directly, coupling a variational autoencoder with multi‐objective optimization and active learning to progressively expand the validated design domain. The discovered nano‐architectures, realized as pyrolytic carbon by two‐photon lithography, deliver 18–23% higher stiffness and 26–
Jinwook Yeo, Peter Serles, Donggeun Park, Julia R. Greer, Seunghwa Ryu   +4 more
wiley   +1 more source

Flexible Integration of Structurally Diverse Spatial Multi‐Omics With AgaeSMO

Advanced Science, EarlyView.
AgaeSMO is a versatile and robust deep learning framework for flexible cross‐integration of spatial multi‐omics data. Leveraging a GATs network with a graph attention module, it learns joint embedding across diverse modalities, enabling integration of both structurally paired (e.g., spatial transcriptome‐epigenome, transcriptome‐proteome, transcriptome‐
Kunpeng Liu, Jinpo Su, Haotian Zhou, Yilin Shen, Mengke Qin, Yingjie Luo, Tiancai Wang, Zhenglin Chen, Yuanyuan Wang, Xiaokai Ma   +9 more
wiley   +1 more source