Chung‐Ming Chen

3.7k citations
127 papers · 2.5k indexed · 1 hit paper · h-index 24

Impact in

Papers in

Chung‐Ming Chen

122 papers receiving 2.5k citations

Hit Papers

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans 2016 · 529 citations
5292016202620192022100200300400500

Peers

Chung‐Ming Chen
Comparison fields: 5 of 165
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Health Informatics 60
  • Computer Vision and Pattern Recognition 452
  • Artificial Intelligence 652
  • Pulmonary and Respiratory Medicine 470
Replace Shijun Wang with:
Shijun Wang United States
Gregor Urban United States
Peter Bult Netherlands
Evangelia I. Zacharaki Greece
Lisheng Wang China
David J. Foran United States
Yao Lu China
Caroline Boggis United Kingdom
Yi Gao China
Chung‐Ming Chen relative to Shijun Wang United States Shijun Wang's profile →
Citations per field
00.5×1.5×
Shijun Wang · 1×
Citations per year

Countries citing papers authored by Chung‐Ming Chen

Since Specialization
Citations

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

Fields of papers citing papers by Chung‐Ming Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chung‐Ming Chen. 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 Chung‐Ming Chen. The network helps show where Chung‐Ming Chen may publish in the future.

Co-authors

The 25 scholars most cited alongside Chung‐Ming Chen, 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 Chung‐Ming Chen Line = papers co-authored together Chung‐Ming Chen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20242
4 20244
5 20241
6 20192
7 201824
8 201815
9 20156
10 201518
11 20146
12 201417
13 201247
14 200846
15 200813
16 200712
17 200535
18 2004136
19 200222
20 199810

About Chung‐Ming Chen

Chung‐Ming Chen is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Oral Surgery and Media Technology, having authored 127 papers that have together received 2.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (26 papers), Lung Cancer Diagnosis and Treatment (23 papers), Medical Image Segmentation Techniques (17 papers), AI in cancer detection (16 papers), Medical Imaging Techniques and Applications (14 papers), Bioinformatics and Genomic Networks (9 papers), Advanced X-ray and CT Imaging (8 papers) and Image and Signal Denoising Methods (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.1k citations), Health Informatics (60 citations), Computer Vision and Pattern Recognition (452 citations), Artificial Intelligence (652 citations) and Pulmonary and Respiratory Medicine (470 citations). Chung‐Ming Chen has collaborated with scholars based in Taiwan, United States and China. Frequent co-authors include Yi‐Hong Chou, Yeun‐Chung Chang, Dinggang Shen, Chiun‐Sheng Huang, Jie-Zhi Cheng, Dong Ni, Jing Qin, Chui-Mei Tiu, Jung‐Hsin Lin and Chui‐Mei Tiu. Their work appears in journals such as Scientific Reports, Ultrasound in Medicine & Biology, Annals of Surgical Oncology, Cancers and IEEE Access.

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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