Hong Yan

25.5k citations
960 papers · 17.8k indexed · 3 hit papers · h-index 61

Impact in

Papers in

Hong Yan

900 papers receiving 17.0k citations

Hit Papers

AI in drug discovery and its clinical relevance 2023 · 125 citations
12520112026201620212505007501000

Peers

Hong Yan
Comparison fields: 5 of 226
  • Computational Mathematics 256
  • Computer Vision and Pattern Recognition 5.4k
  • Media Technology 1.3k
  • Cancer Research 1.3k
  • Signal Processing 824
Replace Hui Zou with:
Hui Zou United States
Gunnar Rätsch Germany
Laurens van der Maaten Netherlands
Thomas Hofmann Germany
Tommaso Cai Italy
Jason Weston United States
Brendan J. Frey Canada
Nello Cristianini Brazil
Daphne Koller United States
Lei Zhu China
Hong Yan relative to Hui Zou United States Hui Zou's profile →
Citations per field
00.5×2.6×
Hui Zou · 1×
Citations per year

Countries citing papers authored by Hong Yan

Since Specialization
Citations

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

Fields of papers citing papers by Hong Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Hong Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hong Yan Line = papers co-authored together Hong Yan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20242
4 20244
5 202415
6 20242
7 20240
8 20241
9 20243
10 20235
11 20236
12 20231
13 20238
14 20232
15 20231
16 20231
17
Cortical thinning and flattening in schizophrenia and their unaffected parents
20191
18 201814
19 201612
20 20169

About Hong Yan

Hong Yan is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition, Aging, Media Technology and Signal Processing, having authored 960 papers that have together received 17.8k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (91 papers), Gene expression and cancer classification (82 papers), Bioinformatics and Genomic Networks (63 papers), Medical Image Segmentation Techniques (61 papers), Face and Expression Recognition (60 papers), Machine Learning in Bioinformatics (52 papers), Advanced Image and Video Retrieval Techniques (46 papers) and Handwritten Text Recognition Techniques (45 papers). The work is most often cited by research in Computational Mathematics (256 citations), Computer Vision and Pattern Recognition (5.4k citations), Media Technology (1.3k citations), Cancer Research (1.3k citations) and Signal Processing (824 citations). Hong Yan has collaborated with scholars based in Hong Kong, China and Australia. Frequent co-authors include Alan Wee‐Chung Liew, Kin‐Man Lam, Zheru Chi, Tuan D. Pham, Dao‐Qing Dai, John J. Harding, Kai Huang, Debby D. Wang, Le Ou-Yang and Xiao-Fei Zhang. Their work appears in journals such as Pattern Recognition, Pattern Recognition Letters, Bioinformatics, IEEE/ACM Transactions on Computational Biology and Bioinformatics and BMC Bioinformatics.

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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