Danielle Toussie

726 citations
18 papers · 418 · h-index 6

Impact in

Papers in

Danielle Toussie

17 papers receiving 411 citations

Peers

Danielle Toussie
Comparison fields: 5 of 50
  • Health Informatics 30
  • Critical Care and Intensive Care Medicine 64
  • Radiology, Nuclear Medicine and Imaging 243
  • Infectious Diseases 173
  • Pulmonary and Respiratory Medicine 140
Replace Sayan Manna with:
Sayan Manna United States
Nicholas Voutsinas United States
Yogesh Sean Gupta United States
Young Kyung Lee South Korea
Jose Concepcion United States
Séverine Dangeard France
Yinghua Zhong China
Marcello Petrini Italy
Davide Colombi Italy
Flavio Cesare Bodini Italy
Danielle Toussie relative to Sayan Manna United States Sayan Manna's profile →
Citations per field
00.5×1.5×
Sayan Manna · 1×
Citations per year

Countries citing papers authored by Danielle Toussie

Since Specialization
Citations

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

Fields of papers citing papers by Danielle Toussie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2020230
2 202052
3 202043
4 202041
5 202118
6 20207
7 20205
8 20225
9 20243
10 20223
11 20253
12 20212
13
Appropriate Evaluation of Diagnostic Utility of Machine Learning Algorithm Generated Images
20202
14 20211
15 20241
16 20211
17 20231
18 20250

About Danielle Toussie

Danielle Toussie is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Surgery and Critical Care and Intensive Care Medicine, having authored 18 papers that have together received 418 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (5 papers), Pericarditis and Cardiac Tamponade (4 papers), Pneumothorax, Barotrauma, Emphysema (4 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), Cardiac Imaging and Diagnostics (3 papers), Ultrasound in Clinical Applications (3 papers), COVID-19 Clinical Research Studies (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Health Informatics (30 citations), Critical Care and Intensive Care Medicine (64 citations), Radiology, Nuclear Medicine and Imaging (243 citations), Infectious Diseases (173 citations) and Pulmonary and Respiratory Medicine (140 citations). Danielle Toussie has collaborated with scholars based in United States and Israel. Frequent co-authors include Adam Bernheim, Michael Chung, Adam Jacobi, Nicholas Voutsinas, Mark Finkelstein, Mario A. Cedillo, Corey Eber, Sayan Manna, Samuel Z. Maron and Yogesh Sean Gupta. Their work appears in journals such as Clinics in Chest Medicine, Radiology Artificial Intelligence, Radiology, Radiology Cardiothoracic Imaging and Radiographics.

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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