David A. Mong

4.7k citations
15 papers · 1.8k · 1 hit paper · h-index 5

Impact in

Papers in

David A. Mong

12 papers receiving 1.7k citations

David A. Mong's Hit Papers

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison 2019 · 1.5k citations
1.5k0+2+4Years since publication50010001.5k

Peers

David A. Mong
Comparison fields: 5 of 117
  • Health Informatics 224
  • Radiology, Nuclear Medicine and Imaging 1.0k
  • Artificial Intelligence 1.0k
  • Computer Vision and Pattern Recognition 370
  • Health Information Management 60
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David A. Mong relative to Rashid Mazhar Qatar Rashid Mazhar's profile →
Citations per field
00.5×10.8×
Rashid Mazhar · 1×
Citations per year

Countries citing papers authored by David A. Mong

Since Specialization
Citations

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

Fields of papers citing papers by David A. Mong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David A. Mong. 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 David A. Mong. The network helps show where David A. Mong may publish in the future.

Co-authors

The 25 scholars most cited alongside David A. Mong, 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 David A. Mong Line = papers co-authored together David A. Mong links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
Hit paper breakdown →
20191547
2 2018206
3 201627
4 20207
5 20234
6 20224
7 20213
8 20172
9 20231
10 20221
11 20251
12 20221
13 20230
14 20100
15 20100

About David A. Mong

David A. Mong is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Epidemiology, Critical Care and Intensive Care Medicine and Artificial Intelligence, having authored 15 papers that have together received 1.8k indexed citations. Recurring topics across this work include Machine Learning in Healthcare (2 papers), Ultrasound in Clinical Applications (2 papers), Congenital Diaphragmatic Hernia Studies (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Congenital Heart Disease Studies (2 papers), Neonatal Respiratory Health Research (1 paper), Bone fractures and treatments (1 paper) and Vasculitis and related conditions (1 paper). The work is most often cited by research in Health Informatics (224 citations), Radiology, Nuclear Medicine and Imaging (1.0k citations), Artificial Intelligence (1.0k citations), Computer Vision and Pattern Recognition (370 citations) and Health Information Management (60 citations). David A. Mong has collaborated with scholars based in United States. Frequent co-authors include Curtis P. Langlotz, Matthew P. Lungren, Safwan S. Halabi, David B. Larson, Yifan Yu, Bhavik N. Patel, Richard H. Jones, Pranav Rajpurkar, Michael Ko and Jeremy Irvin. Their work appears in journals such as Seminars in Thoracic and Cardiovascular Surgery, Artificial Intelligence in Medicine, Medical Image Analysis, Pediatric Anesthesia and Pediatric Rheumatology.

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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