Results 141 to 150 of about 681,799 (255)

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source

Comparative Analysis of Deep Learning-Based Feature Extractors for Change Detection in Automotive Radar Maps

IEEE Access
The Siamese network architecture has been applied by deep learning practitioners to find similarities between images. In the domain of autonomous driving, this network configuration has recently gained attention for solving the change detection task ...
Harihara Bharathy Swaminathan, Aron Sommer, Uri Iurgel, Andreas Becker, Martin Atzmueller   +4 more
doaj   +1 more source

scGEN: Leveraging an Adaptive Weighting Strategy for Challenging Cell Clustering in Single‐Cell RNA‐seq

Advanced Science, EarlyView.
scGEN combines attribute–structure encoding, adaptive hard‐sample weighting, and regularized zero‐inflated negative binomial loss to resolve ambiguous single‐cell states. In the developing human pituitary, refined annotations reveal Pre.Gonado cells at 7 weeks and previously obscured developmental communication networks.
Fang Huang, Dayu Hu, Yaqi Dai, Aoyi Geng, Renxiang Guan, Hao Quan, Brett A. McGregor, Zhihan Wang, Nadeem Khan, Hongsheng Zhang, Jinghua Zhang, Mingyang Xia, Xiaoqiong Gu, Di Che, Junguk Hur, Xiaoyu Cui, Kai Guo   +16 more
wiley   +1 more source

MAPA: A Semantic Network Framework for Functional Module Discovery and Interpretation in Multi‐Omics Data

Advanced Science, EarlyView.
MAPA transforms complex multi‐omics data into biologically coherent functional modules by integrating pathway information with molecular interaction networks. Retrieval‐augmented large language models then generate structured, literature‐informed interpretations.
Yifei Ge, Feifan Zhang, Yijiang Liu, Chao Jiang, Peng Gao, Nguan Soon Tan, Sai Zhang, Yuchen Shen, Qianyi Zhou, Xin Zhou, Xiao Wang, Fangqing Zhao, Chuchu Wang, Xiaotao Shen   +13 more
wiley   +1 more source

Predicting Enzyme Turnover Numbers and Enabling Rational Enzyme Evolution

Advanced Science, EarlyView.
MCKcat, a deep learning framework combining multi‐scale convolution and cross‐attention, accurately predicts enzyme turnover number (kcat) by fusing sequence and reaction representations. It couples with rational design in a two‐step strategy for Bacillus aryabhattai laccase engineering, achieving a 75% positive rate with synergistically enhanced ...
Fengya Ge, Xiangyang Ma, Jiyan Li, Mengxiang Wang, Fuping Lu, Yihan Liu, Lin Wang   +6 more
wiley   +1 more source

Semantics [PDF]

Nature Clinical Practice Gastroenterology & Hepatology, 2008
openaire   +2 more sources

DeepLNM: A Multimodal Model for Predicting Lymph Node Metastasis in Colorectal Cancer

Advanced Science, EarlyView.
Traditional diagnosis may miss positive LNM cases, and pathologists face a workload; therefore, we develop DeepLNM, a multimodal model that predicts lymph node metastasis in colorectal cancer from H&E WSIs, CT images, and text. DeepLNM is robust across internal, external, and prospective cohorts and, in a user study, improves diagnostic accuracy while ...
Zhengyu Zhang, Chengyu Lu, Zhen Wang, Zhijian Cen, Yangshu Zhou, Danyi Li, Qi Xie, Bingbing Li, Shujing Guo, Zhijun Gan, Er‐ran Zhu, Jinbang Li, Aihetaimu Aimaier, Rui Mao, Weihao Qiu, Chenglong Zhao, Ying Tan, Xiaolin Liu, Huiting Ma, Tiansu Geng, Peiyue Wu, Huijun Du, Yu Wang, Yueping Liu, Li Liang   +24 more
wiley   +1 more source

Evaluating lexical resources for a semantic tagger [PDF]

, 2004
Semantic lexical resources play an important part in both linguistic study and natural language engineering. In Lancaster, a large semantic lexical resource has been built over the past 14 years, which provides a knowledge base for the USAS semantic ...
Rayson, P., Piao, S, McEnery, AM, Piao, S., Archer, Dawn, Archer, DE, McEnery, A. M., Rayson, P   +7 more
core  

A Facial Foundation Model for Clinical Biomarker Prediction and Real‐World Mobile Deployment

Advanced Science, EarlyView.
MedicalFaceFound is a facial foundation model developed through three‐stage progressive pre‐training, adapting representations from general vision to facial structure and clinical phenotypes. Using a single facial image, it estimates 62 biomarkers across multiple physiological systems and supports downstream risk prediction for cardiovascular ...
Tingfeng Xu, Huixuan Xu, Li Lin, Fei Wang, Yaodong Ding, Shuangqiao Liao, Xingyu Chen, Jichen Wen, Hongqiang Zhao, Jing Hao, Weixiang Zhao, Gong Zhang, Shiguang Shan, Yong Zeng, Hu Han, Minxian Wang   +15 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