Jianhua Yao

20.8k total citations · 4 hit papers
377 papers, 12.7k citations indexed

About

Jianhua Yao is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biomedical Engineering. According to data from OpenAlex, Jianhua Yao has authored 377 papers receiving a total of 12.7k indexed citations (citations by other indexed papers that have themselves been cited), including 139 papers in Radiology, Nuclear Medicine and Imaging, 97 papers in Computer Vision and Pattern Recognition and 82 papers in Biomedical Engineering. Recurrent topics in Jianhua Yao's work include Radiomics and Machine Learning in Medical Imaging (82 papers), Medical Image Segmentation Techniques (59 papers) and Colorectal Cancer Screening and Detection (59 papers). Jianhua Yao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (82 papers), Medical Image Segmentation Techniques (59 papers) and Colorectal Cancer Screening and Detection (59 papers). Jianhua Yao collaborates with scholars based in United States, China and Hong Kong. Jianhua Yao's co-authors include Ronald M. Summers, Le Lü, Daniel J. Mollura, Holger R. Roth, Hoo-Chang Shin, Ziyue Xu, Mingchen Gao, Isabella Nogues, Joseph E. Burns and Xinjian Chen and has published in prestigious journals such as New England Journal of Medicine, Nucleic Acids Research and Nature Communications.

In The Last Decade

Jianhua Yao

362 papers receiving 12.4k 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.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

2016 4.0k citations Jianhua Yao et al. profile →
Improving Computer-Aided Detection UsingConvolutional Neural Networks and Random View Aggregation

2015 417 citations Jianhua Yao et al. profile →
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data

2022 244 citations Fan Yang, Fang Wang et al. profile →
Benchmarking spatial clustering methods with spatially resolved transcriptomics data

2024 66 citations Zhiyuan Yuan, Fangyuan Zhao et al. Nature Methods profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jianhua Yao United States	50	4.5k	3.3k	2.6k	2.1k	1.5k	377	12.7k
Jeroen van der Laak Netherlands	48	7.2k 1.6×	7.8k 2.4×	4.1k 1.6×	2.0k 1.0×	1.9k 1.3×	207	17.0k
Tianfu Wang China	57	3.3k 0.7×	3.3k 1.0×	2.8k 1.1×	3.2k 1.5×	728 0.5×	409	12.3k
Kenji Suzuki Japan	58	3.5k 0.8×	2.0k 0.6×	2.0k 0.8×	1.1k 0.5×	2.3k 1.5×	529	13.4k
Bradley J. Erickson United States	49	4.5k 1.0×	1.8k 0.5×	1.4k 0.5×	1.4k 0.7×	1.5k 1.0×	280	10.4k
Andre Esteva United States	13	3.6k 0.8×	4.9k 1.5×	1.5k 0.6×	1.3k 0.6×	902 0.6×	30	11.9k
Ronald M. Summers United States	62	9.3k 2.0×	5.2k 1.6×	4.3k 1.6×	3.5k 1.6×	3.5k 2.3×	501	18.9k
Le Lü United States	39	4.0k 0.9×	3.3k 1.0×	3.0k 1.1×	1.5k 0.7×	1.2k 0.8×	188	9.8k
Jing Qin China	59	4.1k 0.9×	4.5k 1.4×	5.2k 2.0×	2.1k 1.0×	1.3k 0.8×	527	15.6k
Guang Yang United Kingdom	55	4.7k 1.0×	1.7k 0.5×	2.5k 1.0×	2.0k 1.0×	1.2k 0.8×	449	11.3k
Francesco Ciompi Netherlands	28	6.6k 1.5×	5.7k 1.7×	3.4k 1.3×	1.8k 0.9×	2.1k 1.4×	103	12.6k

Countries citing papers authored by Jianhua Yao

Since Specialization

Citations

This map shows the geographic impact of Jianhua Yao'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 Jianhua Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianhua Yao more than expected).

Fields of papers citing papers by Jianhua Yao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jianhua Yao. 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 Jianhua Yao. The network helps show where Jianhua Yao may publish in the future.

Co-authorship network of co-authors of Jianhua Yao

This figure shows the co-authorship network connecting the top 25 collaborators of Jianhua Yao. A scholar is included among the top collaborators of Jianhua Yao 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 Jianhua Yao. Jianhua Yao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Jiang, Shengdian, Lijun Wang, Zhixi Yun, et al.. (2025). NeuroXiv: AI-powered open databasing and dynamic mining of brain-wide neuron morphometry. Nature Methods. 22(6). 1195–1198.

Huang, Long-Kai, et al.. (2025). Annotation-guided Protein Design with Multi-Level Domain Alignment. 1855–1866. 1 indexed citations

Cui, Yan, Fangyuan Zhao, Zhidong Yang, et al.. (2024). Complete spatially resolved gene expression is not necessary for identifying spatial domains. Cell Genomics. 4(6). 100565–100565. 5 indexed citations

Zhao, Yu, Bing He, Zongbo Han, et al.. (2024). Learning With Noisy Labels Over Imbalanced Subpopulations. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6544–6555. 7 indexed citations

Leung, Howard, et al.. (2024). Deep Spatio-Temporal Network for Low-SNR Cryo-EM Movie Frame Enhancement. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 21(5). 1299–1310. 1 indexed citations

Cai, Jiafa, Fan Zhang, Zhuo Song, et al.. (2024). 1371P An anti-EpCAM x CD3 bispecific antibody, M701, for the treatment of malignant pleural effusion in NSCLC patients: Intermediate results of a prospective multicenter phase Ib trial. Annals of Oncology. 35. S862–S862. 2 indexed citations

Li, Wei, Fan Yang, Fang Wang, et al.. (2024). scPROTEIN: a versatile deep graph contrastive learning framework for single-cell proteomics embedding. Nature Methods. 21(4). 623–634. 16 indexed citations

Zhang, Lingling, Jun Liao, Han Wang, et al.. (2023). Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types. Laboratory Investigation. 103(10). 100212–100212.

Zhu, Zhenkai, et al.. (2023). Superhydrophobic and Anti‐Icing Surface by Femtosecond Laser Direct Writing. Advanced Engineering Materials. 25(20). 10 indexed citations

10.

Zhao, Yu, Bing He, Fan Xu, et al.. (2023). DeepAIR: A deep learning framework for effective integration of sequence and 3D structure to enable adaptive immune receptor analysis. Science Advances. 9(32). eabo5128–eabo5128. 26 indexed citations

11.

Wang, Zhikang, Yue Bi, Xiaoyu Wang, et al.. (2023). Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification. Bioinformatics. 39(3). 14 indexed citations

12.

Ding, Yan, Fan Yang, Yanan Wang, et al.. (2023). Multi-center study on predicting breast cancer lymph node status from core needle biopsy specimens using multi-modal and multi-instance deep learning. npj Breast Cancer. 9(1). 58–58. 8 indexed citations

13.

Wu, Zihan, et al.. (2023). Streamlining spatial omics data analysis with Pysodb. Nature Protocols. 19(3). 831–895. 9 indexed citations

14.

Chen, Mingcai, Yu Zhao, Zhonghuang Wang, Bing He, & Jianhua Yao. (2023). A Noisy-Label-Learning Formulation for Immune Repertoire Classification and Disease-Associated Immune Receptor Sequence Identification. 4739–4747. 1 indexed citations

15.

Wang, Bin, Jiajia Wang, Yunfeng Wang, et al.. (2022). Effects of incidence angle and optimization in femtosecond laser polishing of C/SiC composites. Ceramics International. 48(21). 32290–32304. 25 indexed citations

16.

Wang, Xinran, Liang Wang, Hong Bu, et al.. (2021). How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies. npj Breast Cancer. 7(1). 61–61. 31 indexed citations

17.

Jiang, Shaowei, Chengfei Guo, Pengming Song, et al.. (2021). Resolution-Enhanced Parallel Coded Ptychography for High-Throughput Optical Imaging. ACS Photonics. 8(11). 3261–3271. 53 indexed citations

18.

Fang, Yuqi, Delong Zhu, Jianhua Yao, Yixuan Yuan, & Raymond Kai‐Yu Tong. (2020). ABC-Net: Area-Boundary Constraint Network With Dynamical Feature Selection for Colorectal Polyp Segmentation. IEEE Sensors Journal. 21(10). 11799–11809. 37 indexed citations

19.

Banerjee, Shubhasree, Mohammadhadi Bagheri, Veit Sandfort, et al.. (2018). Vascular calcification in patients with large-vessel vasculitis compared to patients with hyperlipidemia. Seminars in Arthritis and Rheumatism. 48(6). 1068–1073. 24 indexed citations

20.

Yao, Jianhua, Angelo M. Taveira‐DaSilva, Amanda M. Jones, et al.. (2014). Sustained Effects of Sirolimus on Lung Function and Cystic Lung Lesions in Lymphangioleiomyomatosis. American Journal of Respiratory and Critical Care Medicine. 190(11). 1273–1282. 65 indexed citations

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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