English | 繁體

Search in the results

UM

Browse/Search Results:  1-6 of 6 Help

Selected(0)Clear Items/Page:    Sort:
AI-powered interpretable imaging phenotypes noninvasively characterize tumor microenvironment associated with diverse molecular signatures and survival in breast cancer Journal article
Lv, Tianxu, Hong, Xiaoyan, Liu, Yuan, Miao, Kai, Sun, Heng, Li, Lihua, Deng, Chuxia, Jiang, Chunjuan, Pan, Xiang. AI-powered interpretable imaging phenotypes noninvasively characterize tumor microenvironment associated with diverse molecular signatures and survival in breast cancer[J]. Computer Methods and Programs in Biomedicine, 2024, 243, 107857.
Authors:  Lv, Tianxu;  Hong, Xiaoyan;  Liu, Yuan;  Miao, Kai;  Sun, Heng; et al.
Favorite | TC[WOS]:4 TC[Scopus]:4  IF:4.9/5.5 | Submit date：2024/02/22
Breast Cancer  Deep Learning  Interpretable Imaging Phenotypes  Intra-tumor Heterogeneity  Tumor Microenvironment  
Model-driven optimal experimental design for calibrating cardiac electrophysiology models Journal article
Lei,Chon Lok, Clerx,Michael, Gavaghan,David J., Mirams,Gary R.. Model-driven optimal experimental design for calibrating cardiac electrophysiology models[J]. Computer Methods and Programs in Biomedicine, 2023, 240, 107690.
Authors:  Lei,Chon Lok;  Clerx,Michael;  Gavaghan,David J.;  Mirams,Gary R.
Favorite | TC[WOS]:5 TC[Scopus]:5  IF:4.9/5.5 | Submit date：2023/08/03
Action Potential  Electrophysiology  Mathematical Modelling  Model Calibration  Optimal Experimental Design  Patch Clamp  
DARVIC: Dihedral angle-reliant variant impact classifier for functional prediction of missense VUS Journal article
Lagniton,Philip Naderev P., Tam,Benjamin, Wang,San Ming. DARVIC: Dihedral angle-reliant variant impact classifier for functional prediction of missense VUS[J]. Computer Methods and Programs in Biomedicine, 2023, 238, 107596.
Authors:  Lagniton,Philip Naderev P.;  Tam,Benjamin;  Wang,San Ming
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:4.9/5.5 | Submit date：2023/08/03
Dihedral Angles  Human Muty Homolog (Mutyh)  Missense Variants  Molecular Dynamics Simulations (Md Simulations)  Protein Structure  Ramachandran Principle  Tumor Protein 53 (Tp53)  
Deep residual contextual and subpixel convolution network for automated neuronal structure segmentation in micro-connectomics Journal article
Xiao, Chi, Hong, Bei, Liu, Jing, Tang, Yuanyan, Xie, Qiwei, Han, Hua. Deep residual contextual and subpixel convolution network for automated neuronal structure segmentation in micro-connectomics[J]. Computer Methods and Programs in Biomedicine, 2022, 219, 106759.
Authors:  Xiao, Chi;  Hong, Bei;  Liu, Jing;  Tang, Yuanyan;  Xie, Qiwei; et al.
Favorite | TC[WOS]:4 TC[Scopus]:5  IF:4.9/5.5 | Submit date：2022/05/13
Deep Learning  Neuronal Structure Segmentation  Subpixel Convolution  Electron Microscopy  Micro-connectomics  
Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition Journal article
Jialin Tang, Qinglang Su, Binghua Su, Simon Fong, Wei Cao, Xueyuan Gong. Parallel ensemble learning of convolutional neural networks and local binary patterns for face recognition[J]. Computer Methods and Programs in Biomedicine, 2020, 197, 105622.
Authors:  Jialin Tang;  Qinglang Su;  Binghua Su;  Simon Fong;  Wei Cao; et al.
Favorite | TC[WOS]:28 TC[Scopus]:44  IF:4.9/5.5 | Submit date：2021/03/09
Convolutional Neural Networks (Cnn)  Local Binary Patterns (Lbp)  Ensemble Learning  Face Recognition  
White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment Journal article
Tengyue Li, Simon Fong, Shirley W.I. Siu, Xin-she Yang, Lian-Sheng Liu, Sabah Mohammed. White learning methodology: A case study of cancer-related disease factors analysis in real-time PACS environment[J]. Computer Methods and Programs in Biomedicine, 2020, 197.
Authors:  Tengyue Li;  Simon Fong;  Shirley W.I. Siu;  Xin-she Yang;  Lian-Sheng Liu; et al.
Favorite | TC[WOS]:4 TC[Scopus]:4  IF:4.9/5.5 | Submit date：2021/03/09
Data Mining Methodology  Deep Learning  Bayesian Network  Radiological Data Analysis