Matthew P. Lungren

19.7k citations
96 papers · 6.1k indexed · 6 hit papers · h-index 36
Topics
Artificial Intelligence in Healthcare and Education (33 papers)Radiomics and Machine Learning in Medical Imaging (27 papers)COVID-19 diagnosis using AI (24 papers)
Journals
New England Journal of MedicineNature CommunicationsSHILAP Revista de lepidopterología

In The Last Decade

Matthew P. Lungren

93 papers receiving 5.9k citations

Hit Papers

MIMIC-CXR, a de-identified publicly available database of...201920262021202320192020202020242023250500750

Peers

Matthew P. Lungren
Comparison fields: 5 of 176
  • Radiology, Nuclear Medicine and Imaging 2.9k
  • Artificial Intelligence 2.3k
  • Health Informatics 1.4k
  • Computer Vision and Pattern Recognition 779
  • Biomedical Engineering 774
Replace Eyal Klang with:
Eyal Klang Israel
Curtis P. Langlotz United States
Pranav Rajpurkar United States
Bradley J. Erickson United States
Daniel L. Rubin United States
Luca Saba Italy
Benjamin S. Glicksberg United States
Marcus R. Makowski Germany
Eli Konen Israel
Chintan Parmar United States
Matthew P. Lungren relative to Eyal Klang Israel Eyal Klang's profile →
Citations per field
00.5×1.6×
Eyal Klang · 1×
Citations per year

Countries citing papers authored by Matthew P. Lungren

Since Specialization
Citations

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

Fields of papers citing papers by Matthew P. Lungren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew P. Lungren. 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 Matthew P. Lungren. The network helps show where Matthew P. Lungren may publish in the future.

Co-authorship network of co-authors of Matthew P. Lungren

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew P. Lungren. A scholar is included among the top collaborators of Matthew P. Lungren 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 Matthew P. Lungren. Matthew P. Lungren is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 5
2 6
3
TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformersbreakdown →
287
4 3
5
Self-supervised learning for medical image classification: a systematic review and implementation guidelinesbreakdown →
174
6 107
7 18
8 70
9 12
10
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays.
2
11
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays
0
12 10
13 103
14 47
15 89
16
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelinesbreakdown →
448
17 140
18
MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reportsbreakdown →
773
19
Overview of ImageCLEF 2018 Medical Domain Visual Question Answering Task.
26
20 25

About Matthew P. Lungren

Matthew P. Lungren is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Internal Medicine, having authored 96 papers that have together received 6.1k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (33 papers), Radiomics and Machine Learning in Medical Imaging (27 papers) and COVID-19 diagnosis using AI (24 papers). The work is most often cited by research in Health Informatics (1.4k citations), Radiology, Nuclear Medicine and Imaging (2.9k citations) and Artificial Intelligence (2.3k citations). Matthew P. Lungren has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Shih-Cheng Huang, Anuj Pareek, Curtis P. Langlotz, Pranav Rajpurkar, Imon Banerjee, Daniel L. Rubin, David B. Larson, Seth J. Berkowitz, Chih-Ying Deng and Alistair E. W. Johnson. Their work appears in journals such as New England Journal of Medicine, Nature Communications and SHILAP Revista de lepidopterología.

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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