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BIBM 2023: Istanbul, Turkey
- Xingpeng Jiang, Haiying Wang, Reda Alhajj, Xiaohua Hu, Felix Engel, Mufti Mahmud, Nadia Pisanti, Xuefeng Cui, Hong Song:
IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023, Istanbul, Turkiye, December 5-8, 2023. IEEE 2023, ISBN 979-8-3503-3748-8 - Mingjing Han, Yanbin Yin, Han Zhang, Huan Wang:
Hierarchical Semantic Augmentation Graph Neural Network for Drug-Disease Association Prediction. i-viii - Melisa Ece Zeylan, Attila Gürsoy, Simge Senyuz, Ozlem Keskin:
The interaction between mutated DYRK1A and APP suggests a potential target for vascular cognitive impairment. 1-7 - Yihang Bao, Yuanzhao Guo, Wenjie Li, Guan Ning Lin, Zehua Sun, Han Wang:
Probing Transmembrane Proteins Binding Domain via Multi-level Molecule Learning. 5-10 - Jie Chen, Yurong Qian, Zhijian Huang, Xiaojun Xiao, Lei Deng:
Enhancing Protein Solubility Prediction through Pre-trained Language Models and Graph Convolutional Neural Networks. 11-16 - Yihan Dong, Xiaowen Hu, Zhijian Huang, Lei Deng:
TGC-ARG: Predicting Antibiotic Resistance through Transformer-based Modeling and Contrastive Learning. 17-22 - Ruiqi Liu, Zilong Zhang
, Xiuhao Fu, Shankai Yan, Feifei Cui:
AIPPT: Predicts anti-inflammatory peptides using the most characteristic subset of bases and sequences by stacking ensemble learning strategies. 23-29 - Yuyan Shuai, Wenkang Wang, Yiming Li, Min Zeng
, Min Li:
Protein function prediction using graph neural network with multi-type biological knowledge. 30-35 - Chengcheng Sun, Haitao Jiang, Daming Zhu:
Improved Approximation Algorithms for Sorting Unsigned Genomes by Reversals. 36-42 - Nhat C. Tran
, Jean X. Gao:
Integrating Heterogeneous Biological Networks and Ontologies for Improved Protein Function Prediction with Graph Neural Networks. 43-48 - Zhang Wan, Zhuoyi Lin, Shamima Rashid, Shaun Yue-Hao Ng, Rui Yin, J. Senthilnath, Chee Keong Kwoh:
PESI: Paratope-Epitope Set Interaction for SARS-CoV-2 Neutralization Prediction. 49-56 - Shaokai Wang, Bin Ma:
Deep learning boosted amyloidosis diagnosis. 57-62 - Han Wang, Jingtong Zhao, Shengkun Wang, Zhiquan He, Xike Ouyang, Ting Gao:
Predicting Protein-Ligand Binding Affinity with Multi-Scale Structural Features. 63-68 - Yang Xiao, Yueshan Huang, Yu Zhao, Fan Xu, Qin Ren, Bing He, Jianhua Yao, Xiao Liu:
Multimodal-AIR-BERT: A Multimodal Pre-trained Model for Antigen Specificity Prediction in Adaptive Immune Receptors. 69-75 - Wenwu Zeng
, Dafeng Lv, Xuan Liu, Guo Chen, Wenjuan Liu, Shaoliang Peng:
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learning. 76-81 - Qiang Zhang, Juan Liu, Feng Yang, Zhihui Yang, Jing Feng:
SLPFA: Protein Structure-Label Embedding Attention Network for Protein Function Annotation. 82-87 - Avik Bhattacharya
, James O. Wrabl, Samuel J. Landry, Ramgopal R. Mettu:
Parallel Computation of Conformational Stability for CD4+ T-cell Epitope Prediction. 88-93 - Chanaka Bulathsinghalage, Lu Liu:
scHi-CNN: a Computational Method for Statistically Significant Single-cell Hi-C Chromatin Interactions with Nearest Neighbors. 94-99 - Huiyuan Chen, Weiting Chen, Yiqing Zhang, Na Li:
Multi-granularity Information Flow Enhanced Skeleton-based Infant Seizure Detection. 100-103 - Thulani Hewavithana
, Chu Shin Koh, Avleen Kaur
, Raymond J. Spiteri
, Isobel Parkin, Lingling Jin
:
Inference of subgenomes resulting from polyploid events using synteny based dynamic linking and maximum neighbourhood. 104-109 - Bing Jia, Tao Feng, Chenri Li, Baoqi Huang, Fei Hao, Dongjun Liu:
DeepLA: A deep learning-based model for predicting protein function from protein sequence and evolutionary information. 110-113 - Indika Kahanda, Buwani Manuweera, Brendan Mumey, Thiruvarangan Ramaraj, Alan M. Cleary, Joann Mudge:
Genotype-to-Phenotype Associations with Frequented Region Variants. 114-119 - Deqin Liu, Sheng Chen, Shuangjia Zheng, Sen Zhang, Yuedong Yang:
SE(3) Equivalent Graph Attention Network as an Energy-Based Model for Protein Side Chain Conformation. 120-123 - Yongchang Liu, Peiying Li, Shikui Tu, Lei Xu:
PEST: A General-Purpose Protein Embedding Model for Homology Search. 124-127 - Luhan Shen, Chengxin He, Haiying Wang, Yuening Qu, Lei Duan:
DARE: Sequence-Structure Dual-Aware Encoder for RNA-Protein Binding Prediction. 128-131 - Xun Wang, Peng Qu
, Xiangyu Meng, Qing Yang, Lian Qiao, Chaogang Zhang, Xianjin Xie:
MulAxialGO: Multi-Modal Feature-Enhanced Deep Learning Model for Protein Function Prediction. 132-137 - Yan Wang, Ruyi Zhang, XiuQin Xu, Ying Xie, Min Zhao:
Effects of Chronic unpredictability stress on thymus by RNA-seq. 138-141 - Yanju Zhang, Wangjing Qi, Ruohan Lin, Jinli Fan:
SpliceCannon: A novel framework for the prediction of canonical and non-canonical splice sites based on deep learning. 142-146 - Jin A, Ju Xiang, Min Li:
DyNRW: Time-Series Dynamical Networks for Identifying HCC-Related Genes. 147-152 - Tian Bai, Chu Li, Xinyue Peng, Haotian Guan, Zefan Zhang
, Guishen Wang
:
A Novel Drug-Drug Interaction Prediction Model Based on Line Subgraph Generation Strategy. 153-158 - Xiaowen Hu, Yuanpeng Zhang, Jiaxuan Zhang, Lei Deng:
CLPiDA: A Contrastive Learning Approach for Predicting Potential PiRNA-Disease Associations. 159-164 - Yi Jia, Shanshan Zheng, Tingting He, Xingpeng Jiang:
Predicting Microbe-Metabolite Interactions by Integrating Non-negative Matrix Factorization and Generative Network. 165-170 - Xingyi Li, Xuequn Shang, Zhelin Zhao, Chenzhuo Yan:
A personalized pathway activation inference method based on pathway structure for classification of inflammatory bowel disease. 171-176 - Qianqian Peng, Zhihan He, Shichao Liu, Xinzhi Yao, Jingbo Xia:
Integrating Multi-omics Data into A Gated Graph Convolutional Networks for Identifying Cancer Driver Genes and Function Modules. 177-182 - Tongtong Ren, Guohua Wang:
Co-clustering of single-cell RNA-seq data based on weighted non-negative matrix tri-factorization combined with consensus clustering. 183-190 - Xiaojun Xiao, Yurong Qian, Zhijian Huang, Rongtao Zheng, Lei Deng:
Predicting Associations between circRNAs and Drug Sensitivity using Heterogeneous Graphs and Graph Attention Networks. 191-196 - Junfeng Xie, Dafang Zhang, Wei Li:
DeepEAG: A deep learning-based hybrid framework for identifying epilepsy-associated genes using a stacking strategy. 197-202 - Liang Yu, Huan Zhu, Da Dong, Lin Gao:
Gene Expression Profile Prediction under Drug Action Based on Generative Adversarial Networks. 203-208 - Yuanpeng Zhang, Yurong Qian, Xiaojun Xiao, Xiaowen Hu, Zhijian Huang, Lei Deng:
PTDA-SWGCL: Predicting tRNA-Disease Associations using Supplementarily Weighted Graph Contrastive Learning. 209-214 - Ruiqing Zheng, Yanping Zeng, Weixing Zeng, Min Li:
A flexible gene regulatory network reconstruction method based on autoencoder and graph attention network. 215-221 - Christopher H. Fok, Wai-Ki Ching, Chi-Wing Wong:
The Construction of Sparse Probabilistic Boolean Networks: A Discrete Perspective. 222-227 - Kang Jiang, Bo Liao, Petros Papagerakis
, Fang-Xiang Wu:
Imputing single-cell RNA-seq data by graph autoencoder with multi-kernel. 228-232 - Wen-Yue Kang, Chun-Hou Zheng, Ying-Lian Gao, Juan Wang, Junliang Shang, Jin-Xing Liu:
GRPGAT: Predicting CircRNA-disease Associations Based on Graph Random Propagation Network and Graph Attention Network. 233-236 - Desheng Kong, Xu Jin, Maoqiang Xie, MingMing Liu, Yanhao Li, Jingjing He, Hao Shi, Yiran Wan, Yalou Huang, Weiwei Yang:
A Heterogeneous Ranking Contrastive Learning Method for Drug-Target Interaction Prediction. 237-240 - Shengzhi Lai
, Ning Li, Weichuan Yu:
Combining Tags of Various Lengths Benefits Peptide Identification in Bottom-up Proteomics. 241-246 - Jie Li, Bingbo Wang, Jiaqi Li:
A Network Propagation Based Approach for Measuring Cell-Cell Similarity. 247-250 - Yajun Liu, Ru Li, Aimin Li, Rong Fei, Guo Xie, Fang-Xiang Wu:
Prediction of piRNA-mRNA interactions based on an interactive inference network. 251-254 - Yue Liu, Yang Hu, Yadong Wang:
IRPRI: An immune-related prognostic risk indicator for patients with lymphatic invasive colon cancer. 255-259 - Shihao Xia, Jun Meng, Zhaowei Wang
, Yu Wang, Haibin Li, Zhaojing Qin, Yushi Luan:
A multi-granularity information-enhanced pre-training method for predicting the coding potential of sORFs in plant lncRNAs. 260-263 - Tao Yang, Minghua Wang, Xiaoke Ma:
Transfer Learning Classification Algorithm by Exploiting Multi-source Adaptation and Similarity of Omic Data. 264-268 - Yijia Chen, Yiwen Chen, Shanling Nie, Hai Yang:
PMMVar: Leveraging Multi-level Protein Structures for Enhanced Coding Variant Pathogenicity Prediction. 269-274 - Jiayi Dong, Fei Wang:
GROD: Joint Inference of Gene Regulatory Networks and Data Imputation in Single-Cell RNA Sequencing with Temporal Consideration. 275-280 - Cuiyuan Li, Fa Zhang, Kai Hu, Xuefeng Cui:
Variational Clustering and Denoising of Spatial Transcriptomics. 281-286 - Wei Peng, Zhihao Zhang, Wei Dai, Xiaodong Fu, Li Liu, Lijun Liu, Ning Yu:
A multi-view comparative learning method for spatial transcriptomics data clustering. 287-292 - Yunyun Su, Feifei Cui, Shiyu Yan, Quan Zou, Chen Cao, Zilong Zhang
:
Human-Spa: An Online Platform Based on Spatial Transcriptome Data for Diseases of Human Systems. 293-298 - Xiaofeng Wang, Jiahao Zhang, Jianyu Zhou:
Diffusion-Enhanced Graph Attention Network for Cancer Type Classification. 299-305 - Yongshuai Wang, Xiaojun Cai, Defeng Li, Shiwei Sun, Cheng Chen, Xuefeng Cui:
Learned Fingerprint Embedding for Large-Scale Peptide Mass Spectra Retrieval. 306-311 - Meng Yuan
, Seppe Goovaerts, Hanne Hoskens
, Stephen Richmond, Susan Walsh, Mark D. Shriver, John R. Shaffer, Mary L. Marazita, Seth M. Weinberg, Hilde Peeters, Peter Claes
:
Data-driven trait heritability-based extraction of human facial phenotypes. 312-319 - Xiang Chen, Junnan Yu, Li Peng, Min Li:
A deep graph convolution network with attention for clustering scRNA-seq data. 320-323 - Zhipeng Hu, Gaoshi Li, Jingli Wu, Xinlong Luo, Jiafei Liu, Wei Peng, Xiaoshu Zhu:
Essential proteins identification based on weak consensus model and neighborhood aggregation centrality. 324-327 - Nikita Kohli
, Jabed H. Tomal, Yan Yan:
Identification of Important SNPs using Bayesian Deep Learning on Whole-Genome Arabidopsis thaliana Data. 328-332 - Weiguo Li, Junchi Ma, Cuiyuan Li, Ting Yu, Xuefeng Cui:
Using Deep Learning to Classify Full-Length Transcriptome Sequences. 333-338 - Yadong Liu, Hongzhe Guo, Zhenhao Lu, Yadong Wang, Zhongyu Liu, Tao Jiang:
Comprehensive evaluation of RNA-seq alignment methods based on long-read sequencing data. 339-342 - Lorenzo Martini
, Roberta Bardini, Alessandro Savino
, Stefano Di Carlo:
GRAIGH: Gene Regulation accessibility integrating GeneHancer database. 343-348 - Yuyang Wang, Haitao Jiang, Haodi Feng, Daming Zhu:
Minimize Maximum Coverage of Fragment Alignment Selection. 349-354 - Shilin Zhang, Qingchen Zhang:
ADCL: an adaptive dual contrastive learning framework based on MHGAT and VAE for cell type deconvolution in spatial transcriptomics. 355-358 - Yitao Zhou, Fan Yang, Ying Wang, Feng Zeng:
scBERC: A Batch Effect-Removed Clustering method for single-cell omics. 359-364 - Tianci Li, Lulu Xie, Zhonghai Zhang, Xu Li, Bo Duan, Gang Niu, Shiwei Sun, Fa Zhang, Runting Zhang, Guangming Tan, Chunming Zhang:
Integrative Drug Discovery Platform: A Modular Approach for Efficient and Automated Virtual Screening. 365-372 - Yanmin Liu, Xuan Zhang, Wei Zhao, Daming Zhu, Xuefeng Cui:
De Novo Molecular Structure Generation from Mass Spectra. 373-378 - Changsheng Ma
, Qiang Yang
, Shangsong Liang, Xin Gao:
A Distribution Preserving Model for Molecular Graph Generation. 379-386 - Shuoying Wei, Songquan Li, Yifei Guo, Lida Zhu, Xinlong Wen, Rongbo Zhu:
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction. 387-394 - Wenting Ye, Chen Li
, Yang Xie, Wen Zhang, Hong-Yu Zhang, Bowen Wang, Debo Cheng
, Zaiwen Feng:
Causal Intervention for Measuring Confidence in Drug-Target Interaction Prediction. 395-400 - Jiahui Zhang, Jiahe Li, Wenjie Du, Shuai Zhang, Di Wu, Yang Wang:
Improving efficiency in rationale discovery for Out-of-Distribution molecular representations. 401-407 - Bing-Xue Du, Haoyang Yu, Bei Zhu, Yahui Long, Min Wu, Jian-Yu Shi:
GELKcat: An Integration Learning of Substrate Graph with Enzyme Embedding for Kcat prediction. 408-411 - Justin Jose, Ujjaini Alam, Divye Singh, Pooja Arora:
PandoraRLO: Unveiling Protein-Ligand Interactions with Reinforcement Learning for Optimized Pose Prediction. 412-417 - Wenjun Li, Yiqiang Zhou, Xiwei Tang:
TF-DTA: A Deep Learning Approach Using Transformer Encoder to Predict Drug-Target Binding Affinity. 418-421 - Xuan Lin
, Qi Wen
, Sijie Yang, Zu-Guo Yu, Yahui Long, Xiangxiang Zeng:
Interpretable multi-view attention network for drug-drug interaction prediction. 422-427 - Kun-Yu Ni, Yu Huang, Rongkang Xu, Xiao-Mei Wei:
Enhancing Drug Repositioning through Contrastive Learning and Denoised Negative Sampling. 428-431 - Yuzhong Peng, Hao Zhang, Ziqiao Zhang, Yanmei Lin, Shuigeng Zhou, Shaojie Qiao:
GEP-DL4Mol: A Novel Molecular Deep-learning Model Optimization Framework for Boosting Molecular Properties Prediction*. 432-435 - Jialan Tang, Weilin Chen, Xiaoting Zeng, Chuan-Ming Liu, Pingkang Li, Baiying Lei:
GTDDA: Graph Convolutional Network and Graph Transformer Structure for Drug Repositioning. 436-439 - Yuchen Zhang, Linghang Lian, Xuhua Yang:
NrGe-DTL: a computational framework for cancer drug response prediction based on deep transfer learning from combined denoised genomic profiles and chemical structure embedding of drugs. 440-445 - Qinglian Zhu, Xiaoli Lin, Xiaolong Zhang:
Generating Molecules Conditional on 3D Protein Pockets with HGAF. 446-449 - Ho Bae, Heonseok Ha, Siwon Kim:
Privacy-Preserving Publishing of Individual-Level Medical Data for Cloud Services. 456-461 - Ümit Mert Çaglar, Alperen Inci, Oguz Hanoglu, Görkem Polat, Alptekin Temizel:
Ulcerative Colitis Mayo Endoscopic Scoring Classification with Active Learning and Generative Data Augmentation. 462-467 - Wen Cao, Yang Chen, Jian-Ye Yang, Fei-Yang Xue, Zhan-Hui Yu, Jing Feng, Ze-Jun Wu, Jing Gong, Xiaohui Niu:
Metapath-aggregated multilevel graph embedding for miRNA‒disease association prediction. 468-473 - Shuang Chu, Guihua Duan, Cheng Yan:
Predicting miRNA-disease associations based on graph convolutional network with path learning. 474-479 - Jamie Deng, Yusen Wu
, Hilary Hayssen, Brian Englum, Aman Kankaria, Minerva Mayorga-Carlin, Shalini Sahoo, John Sorkin, Brajesh Lal, Yelena Yesha, Phuong Nguyen:
Improving VTE Identification through Adaptive NLP Model Selection and Clinical Expert Rule-based Classifier from Radiology Reports. 480-487 - Yutao Dou, Yangtao Zheng, Dazheng Liu, Keqin Li, Sheng Xiao, Shaoliang Peng:
ParaMET: A Parallel Framework for Efficient Medical Data Extraction on Tianhe-NG Supercomputer. 488-493 - Zhihua Du, Tianyou Huang, Jian-Qiang Li, Vladimir N. Uversky:
TFBSnet: A deep learning-based tool for predicting transcription factor binding site from DNA sequences. 494-499 - Jiaxin Duan, Fengyu Lu, Junfei Liu:
MVP: Optimizing Multi-view Prompts for Medical Dialogue Summarization. 500-507 - Fan Gao, Yuanbo He, Shuai Li, Aimin Hao, Desen Cao:
Diffusing Coupling High-Frequency-Purifying Structure Feature Extraction for Brain Multimodal Registration. 508-515 - Yifan Gao, Jun Li, Xinyue Chang, Yulong Zhang, Riqing Chen, Changcai Yang, Yi Wei, Heng Dong, Lifang Wei:
Morphological Guided Causal Constraint Network for Medical Image Multi-Object Segmentation. 516-521 - Kuo Guo, Yifan Li, Hao Chen, Hong-Bin Shen, Yang Yang:
Isoform Function Prediction Based on Heterogeneous Graph Attention Networks. 522-527 - Xingli Guo, Liang Lu, Yun Yao, Lin Gao:
Mining disease-associated genes based on heterogeneous graph transformer. 528-533 - Zebei Han, Gufeng Yu, Yang Yang:
Enhancing Cancer Gene Prediction through Aligned Fusion of Multiple PPI Networks Using Graph Transformer Models. 542-547 - Chengxin He, Lei Duan, Huiru Zheng, Yuening Qu, Zhenyang Yu:
SIDE: Sequence-Interaction-Aware Dual Encoder for Predicting circRNA Back-Splicing Events. 548-553 - Yabin Kuang
, Minzhu Xie:
Subtype-DCGCN: an unsupervised approach for cancer subtype diagnosis based on multi-omics data. 554-559 - Shuzhong Lai, Zepeng Li:
Detection of potential anxiety in social media based on multimodal fusion with deep learning methods. 560-566 - Xingyun Li, Lin Lu, Xinyu Yi, Hao Wang, Yunshao Zheng
, Yanhong Yu, Qingxiang Wang:
LI-FPN: Depression and Anxiety Detection from Learning and Imitation. 567-573 - Jianghang Liu, Juan Liu, Zhihui Yang, Feng Yang, Qiang Zhang:
AMTL-RFC:A multi-task learning based method for evaluating the feasibility of enzymatic reactions. 574-579 - Yuhang Liu, Tianhao Li, Zixuan Wang, Guiquan Zhu, Yongqing Zhang, Quan Zou:
Exploring Parameter-Efficient Fine-Tuning of a Large-Scale Pre-Trained Model for scRNA-seq Cell Type Annotation. 580-585 - Jun Long, Junkun Hong, Zidong Wang, Tingxuan Chen, Yunfei Chen, Yang Liu:
SPHASE: Multi-Modal and Multi-Branch Surgical Phase Segmentation Framework based on Temporal Convolutional Network. 586-593 - Chayan Maitra, Dibyendu Bikash Seal, Vivek Das, Yevgeniy Vorobeychik, Rajat K. De:
UMINT-FS: UMINT-guided Feature Selection for multi-omics datasets. 594-601 - Shuang Peng, Fei Yang, Ning Sun
, Sheng Chen, Yanfeng Jiang, Aimin Pan:
Exploring Post-Training Quantization of Protein Language Models. 602-608 - Fei Qi, Junyu Li, Yi Liao, Wenxiong Liao, Jiazhou Chen, Hongmin Cai:
Multi-Kernel Tensor Fusion on Grassmann Manifold for Genomic Data Clustering. 609-615 - Muheng Shang, Yan Yang, Minjianan Zhang, Jin Zhang, Duo Xi, Lei Guo, Lei Du:
Identifying Disease-related Brain Imaging Quantitative Traits and Related Genetic Variations via A Bidirectional Association Learning Method. 616-621 - Nan Sheng
, Lan Huang, Yan Wang, Ling Gao, Huiyan Sun, Xuping Xie:
Contrastive self-supervised graph convolutional network for detecting the relationship among lncRNAs, miRNAs, and diseases. 622-629 - Tianyi Shi, Xiucai Ye, Tetsuya Sakurai:
Multi-omics clustering based on interpretable and discriminative features for cancer subtyping. 630-635 - Zhaoyang Sun, Ying Liu, Pei Liu, Wanwan Shi, Jiawei Luo:
scSRL: Siamese Representation Learning-based method for analyzing single-cell RNA-seq data. 636-641 - Suixue Wang, Xiangjun Hu, Qingchen Zhang:
HC-MAE: Hierarchical Cross-attention Masked Autoencoder Integrating Histopathological Images and Multi-omics for Cancer Survival Prediction. 642-647 - Shuang Wang, Jin-Xing Liu, Bao-Min Liu, Ling-Yun Dai, Feng Li, Ying-Lian Gao:
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes. 648-653 - Xingyu Wang, Junzhong Ji:
Adaptive particle swarm architecture search based on multi-level convolutions for functional brain network classification. 654-659 - Yixin Wang, Wenxin Yu, Zhiqiang Zhang, Jun Gong, Peng Chen, Chang Liu:
R2L-Net: Rapid Medical Image Segmentation Network Regularized by Self-Supervised Relative Localization Task. 660-665 - Xiaojie Wang, Jing Xia, Shanshan Gao, Xingwei Hao, Yuanfeng Zhou:
Deep Residual Fourier and Self-Attention for Arbitrary Scale MRI Super-Resolution. 666-671 - Yike Wang, Huifang Ma, Zihao Gao, Zhixin Li, Liang Chang:
BACON: Boundary-guided Polypharmacy Side Effect Prediction via Integrating Molecular Structures and Biochemical Information. 672-677 - Yunzhan Wang, Jin Yang, Yunpeng Cai:
VirusBERTHP: Improved Virus Host Prediction Via Attention-based Pre-trained Model Using Viral Genomic Sequences. 678-683 - Zhenggui Xiang
:
A Transformer-based Patient Clustering Method in Continuing Care Retirement Communities. 684-689