Yuebin Liang

737 total citations · 1 hit paper
13 papers, 524 citations indexed

About

Yuebin Liang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Yuebin Liang has authored 13 papers receiving a total of 524 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Artificial Intelligence and 4 papers in Molecular Biology. Recurrent topics in Yuebin Liang's work include Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (6 papers) and Lung Cancer Diagnosis and Treatment (2 papers). Yuebin Liang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (6 papers) and Lung Cancer Diagnosis and Treatment (2 papers). Yuebin Liang collaborates with scholars based in China. Yuebin Liang's co-authors include Geng Tian, Jialiang Yang, Binbin Ji, Jidong Lang, Binsheng He, Pingping Bing, Songlin Gao, Peng Yuan, Lei Guo and Zixuan Yang and has published in prestigious journals such as BMC Genomics, Journal of Cellular and Molecular Medicine and Briefings in Bioinformatics.

In The Last Decade

Yuebin Liang

13 papers receiving 510 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Prediction of HER2-positive breast cancer recurrence and metastasis risk from histopathological images and clinical information via multimodal deep learning

2021 158 citations Jialiang Yang, Lei Guo et al. Computational and Structural Biotechnology Journal profile →

Peers

Countries citing papers authored by Yuebin Liang

Since Specialization

Citations

This map shows the geographic impact of Yuebin Liang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yuebin Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuebin Liang more than expected).

Fields of papers citing papers by Yuebin Liang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuebin Liang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yuebin Liang. The network helps show where Yuebin Liang may publish in the future.

Co-authorship network of co-authors of Yuebin Liang

This figure shows the co-authorship network connecting the top 25 collaborators of Yuebin Liang. A scholar is included among the top collaborators of Yuebin Liang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yuebin Liang. Yuebin Liang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	Genomic and resistome analysis of Alcaligenes faecalis strain PGB1 by Nanopore MinION and Illumina Technologies 2022 ·BMC Genomics ·Jidong Lang, Yanju Li, Wenjuan Yang, (unknown), Yuebin Liang, Jia Liu, (unknown), Weiwei Wang, Binbin Ji, Geng Tian, Nanying Che, Bo Meng	11
2	ICSDA: a multi-modal deep learning model to predict breast cancer recurrence and metastasis risk by integrating pathological, clinical and gene expression data 2022 ·Briefings in Bioinformatics ·Yuhua Yao, (unknown), Ling Tong, Yuebin Liang, (unknown), Binbin Ji, (unknown), Ling Li, Geng Tian, Min Tang, Xiyue Hu, (unknown), Jialiang Yang	39
3	Computational drug repositioning using similarity constrained weight regularization matrix factorization: A case of COVID‐19 2022 ·Journal of Cellular and Molecular Medicine ·Junlin Xu, Yajie Meng, Lihong Peng, Lijun Cai, Xianfang Tang, Yuebin Liang, Geng Tian, Jialiang Yang	16
4	Evaluating the Risk of Breast Cancer Recurrence and Metastasis After Adjuvant Tamoxifen Therapy by Integrating Polymorphisms in Cytochrome P450 Genes and Clinicopathological Characteristics 2021 ·Frontiers in Oncology ·Hui Pang, Guoqiang Zhang, Na Yan, Jidong Lang, Yuebin Liang, Xinyuan Xu, (unknown), (unknown), Xianjun Li, Ming Shan, Xiaoqin Wang, (unknown), Xiangzhi Meng, (unknown), Geng Tian, Li Cai, Dawei Yuan, Xin Wang	2
5	Prediction of HER2-positive breast cancer recurrence and metastasis risk from histopathological images and clinical information via multimodal deep learning breakdown → 2021 ·Computational and Structural Biotechnology Journal ·Jialiang Yang, (unknown), Lei Guo, Binbin Ji, (unknown), Zixuan Yang, Songlin Gao, Yuan Xu, Geng Tian, Yuebin Liang, Peng Yuan	158
6	Evaluating Cancer-Related Biomarkers Based on Pathological Images: A Systematic Review 2021 ·Frontiers in Oncology ·Xiaoliang Sunney Xie, Xulin Wang, Yuebin Liang, Jingya Yang, Yan Wu, Li Li, Xin Sun, Pingping Bing, Binsheng He, Geng Tian, Xiaoli Shi	55
7	Identification and Validation of Efficacy of Immunological Therapy for Lung Cancer From Histopathological Images Based on Deep Learning 2021 ·Frontiers in Genetics ·(unknown), Jialiang Yang, Yuebin Liang, Bo Liao, Wen Zhu, Xiaofei Mo, (unknown)	14
8	Cervical Cancer Metastasis and Recurrence Risk Prediction Based on Deep Convolutional Neural Network 2021 ·Current Bioinformatics ·Zixuan Ye, Yunxiang Zhang, Yuebin Liang, Jidong Lang, Xiaoli Zhang, (unknown), (unknown), Geng Tian, (unknown), Jialiang Yang	35
9	DeepLRHE: A Deep Convolutional Neural Network Framework to Evaluate the Risk of Lung Cancer Recurrence and Metastasis From Histopathology Images 2020 ·Frontiers in Genetics ·Zhijun Wu, (unknown), Churong Li, Yongcong Cai, Yuebin Liang, Xiaofei Mo, Qingqing Lu, (unknown), (unknown)	42
10	T Cell Receptor Repertoire Sequencing 2020 ·Methods in molecular biology ·Huixin Lin, Yonggang Peng, Xiangbin Chen, Yuebin Liang, Geng Tian, Jialiang Yang	3
11	A Neural Network Framework for Predicting the Tissue-of-Origin of 15 Common Cancer Types Based on RNA-Seq Data 2020 ·Frontiers in Bioengineering and Biotechnology ·Binsheng He, Yanxiang Zhang, Zhen Zhou, Bo Wang, Yuebin Liang, Jidong Lang, Huixin Lin, Pingping Bing, Lan Yu, Dejun Sun, Huaiqing Luo, Jialiang Yang, Geng Tian	61
12	A New Method for CTC Images Recognition Based on Machine Learning 2020 ·Frontiers in Bioengineering and Biotechnology ·Binsheng He, Qingqing Lu, Jidong Lang, Hai Yu, Chao Peng, Pingping Bing, Shijun Li, Qiliang Zhou, Yuebin Liang, Geng Tian	64
13	Genomic Profiling of Driver Gene Mutations in Chinese Patients With Non-Small Cell Lung Cancer 2019 ·Frontiers in Genetics ·Hongxue Meng, (unknown), Dawei Sun, Yuebin Liang, Jidong Lang, (unknown), Qingqing Lu, Yanxiang Zhang, Yanxin An, Geng Tian, Dawei Yuan, Shidong Xu, Jingshu Geng	24

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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