Ken Chang

5.8k total citations · 1 hit paper
51 papers, 2.2k citations indexed

About

Ken Chang is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Artificial Intelligence. According to data from OpenAlex, Ken Chang has authored 51 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Genetics and 12 papers in Artificial Intelligence. Recurrent topics in Ken Chang's work include Radiomics and Machine Learning in Medical Imaging (17 papers), Glioma Diagnosis and Treatment (12 papers) and AI in cancer detection (11 papers). Ken Chang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (17 papers), Glioma Diagnosis and Treatment (12 papers) and AI in cancer detection (11 papers). Ken Chang collaborates with scholars based in United States, China and Canada. Ken Chang's co-authors include Jayashree Kalpathy–Cramer, Andrew Beers, James M. Brown, Raymond Y. Huang, Michael F. Chiang, J. Peter Campbell, Deniz Erdoğmuş, Stratis Ioannidis, R.V. Paul Chan and Susan Ostmo and has published in prestigious journals such as SHILAP Revista de lepidopterología, NeuroImage and Scientific Reports.

In The Last Decade

Ken Chang

49 papers receiving 2.2k 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.

Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks

2018 396 citations James M. Brown, J. Peter Campbell et al. JAMA Ophthalmology profile →

Peers

Countries citing papers authored by Ken Chang

Since Specialization

Citations

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

Fields of papers citing papers by Ken Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Ken Chang. A scholar is included among the top collaborators of Ken Chang 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 Ken Chang. Ken Chang 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

#	Work	Indexed citations
1	Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation 2023 ·Radiology Artificial Intelligence ·Katharina Hoebel, Christopher P. Bridge, Sara Ahmed, (unknown), Caroline Chung, Raymond Y. Huang, Jason M. Johnson, Albert Kim, (unknown), Ken Chang, Jay Patel, Marco C. Pinho, Tracy T. Batchelor, Bruce R. Rosen, Elizabeth R. Gerstner, Jayashree Kalpathy–Cramer	4
2	ACR’s Connect and AI-LAB technical framework 2022 ·JAMIA Open ·(unknown), Laura P. Coombs, (unknown), (unknown), (unknown), Kendall Schmidt, (unknown), (unknown), (unknown), Ken Chang, Jayashree Kalpathy–Cramer	5
3	Radiomics-Based Machine Learning for Outcome Prediction in a Multicenter Phase II Study of Programmed Death-Ligand 1 Inhibition Immunotherapy for Glioblastoma 2022 ·American Journal of Neuroradiology ·Elizabeth George, (unknown), Ken Chang, Harrison X. Bai, Hugo J.W.L. Aerts, Martin Vallières, David A. Reardon, Raymond Y. Huang	26
4	End-to-end artificial intelligence platform for the management of large vessel occlusions: A preliminary study 2022 ·Journal of Stroke and Cerebrovascular Diseases ·Shujuan Meng, Thi My Linh Tran, Mingzhe Hu, Panpan Wang, Thomas Yi, (unknown), (unknown), (unknown), Zhicheng Jiao, Arko Barman, Uğur Çetintemel, Ken Chang, (unknown), Ferdinand Hui, Ian Pan, Bo Xiao, Li Yang, Hao Zhou, Harrison X. Bai	8
5	Inconsistent Partitioning and Unproductive Feature Associations Yield Idealized Radiomic Models 2022 ·Radiology ·Mishka Gidwani, Ken Chang, Jay Patel, Katharina Hoebel, (unknown), Praveer Singh, Clifton D. Fuller, Jayashree Kalpathy–Cramer	21
6	Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence 2022 ·SHILAP Revista de lepidopterología ·Aaron S. Coyner, Jimmy Chen, Ken Chang, Praveer Singh, Susan Ostmo, R.V. Paul Chan, Michael F. Chiang, Jayashree Kalpathy–Cramer, J. Peter Campbell	25
7	Assessing the Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging 2021 ·Radiology Artificial Intelligence ·Nishanth Arun, Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, (unknown), Katharina Hoebel, Sharut Gupta, Jay Patel, Mishka Gidwani, Julius Adebayo, Matthew Li, Jayashree Kalpathy–Cramer	147
8	Evaluation of RAPNO criteria in medulloblastoma and other leptomeningeal seeding tumors using MRI and clinical data 2020 ·Neuro-Oncology ·Jian Peng, Hao Zhou, Oliver Y. Tang, Ken Chang, Panpan Wang, (unknown), Qin Shen, Jing Wu, (unknown), Sohil H. Patel, (unknown), Ke Jin, Bo Xiao, Jerrold L. Boxerman, Xiaoping Gao, Patrick Y. Wen, Harrison X. Bai, Raymond Y. Huang, Li Yang	5
9	Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs Using Convolutional Siamese Neural Networks 2020 ·Radiology Artificial Intelligence ·Matthew Li, Nishanth Arun, Mishka Gidwani, Ken Chang, Francis Deng, Brent P. Little, Dexter P. Mendoza, Min Lang, Susanna I. Lee, Aileen O’Shea, Anushri Parakh, Praveer Singh, Jayashree Kalpathy–Cramer	105
10	Automatic Machine Learning to Differentiate Pediatric Posterior Fossa Tumors on Routine MR Imaging 2020 ·American Journal of Neuroradiology ·Hao Zhou, (unknown), Oliver Y. Tang, (unknown), (unknown), Ken Chang, Qin Shen, (unknown), Beiji Zou, Bo Xiao, Jerrold L. Boxerman, (unknown), Raymond Y. Huang, Li Yang, Harrison X. Bai, (unknown)	47
11	Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast Density 2020 ·Journal of the American College of Radiology ·Ken Chang, Andrew Beers, (unknown), Jay Patel, Praveer Singh, Nishanth Arun, Katharina Hoebel, Nathan Gaw, (unknown), Etta D. Pisano, (unknown), Laura P. Coombs, Keith J. Dreyer, Bibb Allen, Sheela Agarwal, Jayashree Kalpathy–Cramer	37
12	Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging 2020 ·npj Digital Medicine ·Matthew Li, Ken Chang, (unknown), Connie Y. Chang, Ambrose J. Huang, J. Peter Campbell, James M. Brown, Praveer Singh, Katharina Hoebel, Deniz Erdoğmuş, Stratis Ioannidis, William E. Palmer, Michael F. Chiang, Jayashree Kalpathy–Cramer	77
13	Deep Learning Based on MR Imaging for Predicting Outcome of Uterine Fibroid Embolization 2020 ·Journal of Vascular and Interventional Radiology ·Yongheng Luo, (unknown), Robin Wang, (unknown), Jing Wu, (unknown), Ken Chang, Maureen P. Kohi, Lisa P. Jones, Shilpa Reddy, Zishu Zhang, Harrison X. Bai, Richard D. Shlansky-Goldberg	22
14	Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging 2020 ·European Radiology ·Robin Wang, Yeyu Cai, (unknown), (unknown), (unknown), Ian Pan, Thomas Yi, Thi My Linh Tran, Shaolei Lu, Tao Liu, Ken Chang, Raymond Y. Huang, Paul J. Zhang, Zishu Zhang, Enhua Xiao, Jing Wu, Harrison X. Bai	53
15	Bevacizumab Reduces Permeability and Concurrent Temozolomide Delivery in a Subset of Patients with Recurrent Glioblastoma 2019 ·Clinical Cancer Research ·Elizabeth R. Gerstner, Kyrre E. Emblem, Ken Chang, (unknown), Yi‐Fen Yen, Andrew Beers, Jörg Dietrich, Scott R. Plotkin, Ciprian Catana, Jacob M. Hooker, Dan G. Duda, Bruce R. Rosen, Jayashree Kalpathy–Cramer, Rakesh K. Jain, Tracy T. Batchelor	40
16	Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas 2019 ·Journal of Neuro-Oncology ·Hao Zhou, Ken Chang, Harrison X. Bai, Bo Xiao, Chang Su, Wenya Linda Bi, Paul J. Zhang, Joeky T. Senders, Martin Vallières, Vasileios K. Kavouridis, Alessandro Boaro, Omar Arnaout, Li Yang, Raymond Y. Huang	99
17	Automated Diagnosis of Plus Disease in Retinopathy of Prematurity Using Deep Convolutional Neural Networks breakdown → 2018 ·JAMA Ophthalmology ·James M. Brown, J. Peter Campbell, Andrew Beers, Ken Chang, Susan Ostmo, R.V. Paul Chan, Jennifer Dy, Deniz Erdoğmuş, Stratis Ioannidis, Jayashree Kalpathy–Cramer, Michael F. Chiang	396
18	Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab 2017 ·Neuro-Oncology ·Patrick Großmann, Vivek Narayan, Ken Chang, Rifaquat Rahman, Lauren E. Abrey, David A. Reardon, Lawrence H. Schwartz, Patrick Y. Wen, Brian M. Alexander, Raymond Y. Huang, Hugo J.W.L. Aerts	88
19	AnatomiCuts: Hierarchical clustering of tractography streamlines based on anatomical similarity 2017 ·NeuroImage ·Viviana Siless, Ken Chang, Bruce Fischl, Anastasia Yendiki	46
20	Reconstruction of thermal signals in infrared images reveals sub-cutaneous vasculature and thermogenicity 2014 ·Wei‐Min Liu, Ken Chang, Stephen P. Yoon, Alexander M. Gorbach	1

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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