🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Heang‐Ping Chan

University of Michigan

ORCID: 0000-0001-7777-9006
Computer ScienceMedicineEngineering

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 2%percentile
3.0Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets

Tomography(2020)10.18383/j.tom.2019.00031
Top 9%
2.4DataRank
Top 9%75 citations

Sandy Napel, Arjun Jaggi, Sarah A. Mattonen, Lubomir M. Hadjiiski, Mark Muzi +24 more

Papers

Driven by 21 papers — median percentile 78. Top paper: “Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI”.

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Nature Medicine(2022)10.1038/s41591-022-01772-9
N/A
13.0DataRank · unranked
589 citations

Myura Nagendran, Bruce Campbell, David A. Clifton, Gary S. Collins, Spiros Denaxas +95 more

Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets

Tomography(2020)10.18383/j.tom.2019.00031
Top 9%
2.4DataRank
Top 9%75 citations

Sandy Napel, Arjun Jaggi, Sarah A. Mattonen, Lubomir M. Hadjiiski, Mark Muzi +24 more

Survival Prediction of Patients with Bladder Cancer after Cystectomy Based on Clinical, Radiomics, and Deep-Learning Descriptors

Cancers(2023)10.3390/cancers15174372
N/A
0.789DataRank · unranked
15 citations

Lubomir M. Hadjiiski, John Gormley, Heang‐Ping Chan, Elaine M. Caoili, Richard H. Cohan +4 more

Improved Repeatability of Mouse Tibia Volume Segmentation in Murine Myelofibrosis Model Using Deep Learning

Tomography(2023)10.3390/tomography9020048
Top 35%
0.557DataRank
Top 35%9 citations

Rami F. Mourad, Kevin Heist, Humera Tariq, Heang‐Ping Chan, Brian D. Ross +4 more

AI and machine learning in medical imaging: key points from development to translation

BJR|Artificial Intelligence(2024)10.1093/bjrai/ubae006
N/A
0.494DataRank · unranked
26 citations

Karen Drukker, Amita Shukla‐Dave, Heang‐Ping Chan, Berkman Sahiner, Nicholas Petrick +19 more

Hybrid U‐Net‐based deep learning model for volume segmentation of lung nodules in CT images

Medical Physics(2022)10.1002/mp.15810
N/A
0.483DataRank · unranked
24 citations

Chuan Zhou, Heang‐Ping Chan, Lubomir M. Hadjiiski, Aamer Chughtai, Ella A. Kazerooni +1 more

Enhancing Early Lung Cancer Diagnosis: Predicting Lung Nodule Progression in Follow-Up Low-Dose CT Scan with Deep Generative Model

Cancers(2024)10.3390/cancers16122229
N/A
0.425DataRank · unranked
16 citations

Chuan Zhou, Lei Ying, Heang‐Ping Chan, Elizabeth Lee, Aamer Chughtai +3 more

Evaluating the reliability of large language models for clinical data extraction in bladder cancer prognosis

Scientific Reports(2025)10.1038/s41598-025-27593-7
N/A
0.241DataRank · unranked
4 citations

Lubomir M. Hadjiiski, Grace Bruno, John Gormley, Heang‐Ping Chan, Elaine M. Caoili +6 more

Recursive Training Strategy for a Deep Learning Network for Segmentation of Pathology Nuclei With Incomplete Annotation

IEEE Access(2022)10.1109/access.2022.3172958
N/A
0DataRank · unranked
5 citations

Heang‐Ping Chan, Lubomir M. Hadjiiski, Aamer Chughtai, Chuan Zhou

Deep Convolutional Neural Network With Adversarial Training for Denoising Digital Breast Tomosynthesis Images

IEEE Transactions on Medical Imaging(2021)10.1109/tmi.2021.3066896
N/A
0DataRank · unranked
40 citations

Jeffrey A. Fessler, Heang‐Ping Chan, Mingjie Gao

Pathologic categorization of lung nodules: Radiomic descriptors of CT attenuation distribution patterns of solid and subsolid nodules in low-dose CT

European Journal of Radiology(2020)10.1016/j.ejrad.2020.109106
N/A
0DataRank · unranked
7 citations

Heang‐Ping Chan, Aamer Chughtai, Lubomir M. Hadjiiski, Ella A. Kazerooni, Jun Wei +1 more

Model-based deep CNN-regularized reconstruction for digital breast tomosynthesis with a task-based CNN image assessment approach

Physics in Medicine and Biology(2023)10.1088/1361-6560/ad0eb4
N/A
0DataRank · unranked
5 citations

Jeffrey A. Fessler, Heang‐Ping Chan, Mingjie Gao

Deep learning denoising of digital breast tomosynthesis: Observer performance study of the effect on detection of microcalcifications in breast phantom images

Medical Physics(2023)10.1002/mp.16439
N/A
0DataRank · unranked
4 citations

Mark A. Helvie, Mingjie Gao, Lubomir M. Hadjiiski, Chuan Zhou, Kim Garver +6 more

Potential of AI-assisted analysis of mammograms for extensive intraductal component in invasive breast cancer

European Radiology(2023)10.1007/s00330-023-10449-x
N/A
0DataRank · unranked
1 citations

Heang‐Ping Chan

Artificial intelligence in medicine: mitigating risks and maximizing benefits via quality assurance, quality control, and acceptance testing

BJR|Artificial Intelligence(2024)10.1093/bjrai/ubae003
N/A
0DataRank · unranked
38 citations

Amita Shukla‐Dave, Heang‐Ping Chan, Karen Drukker, Ravi K. Samala, Quan Chen +20 more

Risks of feature leakage and sample size dependencies in deep feature extraction for breast mass classification

Medical Physics(2020)10.1002/mp.14678
N/A
0DataRank · unranked
34 citations

Heang‐Ping Chan, Lubomir M. Hadjiiski, Mark A. Helvie, Ravi K. Samala

Outcome Prediction Using Multi-Modal Information: Integrating Large Language Model-Extracted Clinical Information and Image Analysis

Cancers(2024)10.3390/cancers16132402
N/A
0DataRank · unranked
24 citations

Lubomir M. Hadjiiski, John Gormley, Heang‐Ping Chan, Elaine M. Caoili, Richard H. Cohan +6 more

Effect of Dose Level on Radiologists’ Detection of Microcalcifications in Digital Breast Tomosynthesis: An Observer Study with Breast Phantoms

Academic Radiology(2020)10.1016/j.acra.2020.07.038
N/A
0DataRank · unranked
8 citations

Mark A. Helvie, Katherine A. Klein, Carol McLaughlin, Colleen H. Neal, Rebecca Oudsema +6 more

Leveraging Serial Low-Dose CT Scans in Radiomics-based Reinforcement Learning to Improve Early Diagnosis of Lung Cancer at Baseline Screening

Radiology Cardiothoracic Imaging(2024)10.1148/ryct.230196
N/A
0DataRank · unranked
8 citations

Chuan Zhou, Lei Ying, Elizabeth Lee, Heang‐Ping Chan, Aamer Chughtai +3 more

X-ray source motion blur modeling and deblurring with generative diffusion for digital breast tomosynthesis

Physics in Medicine and Biology(2024)10.1088/1361-6560/ad40f8
N/A
0DataRank · unranked
1 citations

Jeffrey A. Fessler, Heang‐Ping Chan, Mingjie Gao

Computer‐aided diagnosis in the era of deep learning

Medical Physics(2020)10.1002/mp.13764
N/A
0DataRank · unranked
348 citations

Lubomir M. Hadjiiski, Ravi K. Samala, Heang‐Ping Chan