Jennifer Quantius

1.2k citations
14 papers · 951 · h-index 13

Impact in

Papers in

Jennifer Quantius

14 papers receiving 938 citations

Peers

Jennifer Quantius
Comparison fields: 5 of 57
  • Pulmonary and Respiratory Medicine 587
  • Hepatology 62
  • Genetics 42
  • Rehabilitation 25
  • Molecular Biology 221
Replace Tomomi Tadokoro with:
Tomomi Tadokoro Japan
Arun C. Habermann United States
Xiao Hua SHI China
Lesley A. Rabach United States
Lance M. Peter United States
Rohan Verma United States
Zhenhua Yang China
Gianluca Turcatel United States
Jibing Yang United States
Victor M. Tan United States
Jennifer Quantius relative to Tomomi Tadokoro Japan Tomomi Tadokoro's profile →
Citations per field
00.5×2×3.4×
Tomomi Tadokoro · 1×
Citations per year

Countries citing papers authored by Jennifer Quantius

Since Specialization
Citations

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

Fields of papers citing papers by Jennifer Quantius

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

14 of 14 papers shown
#Work
1 2016275
2 2013131
3 2016103
4 201583
5 201765
6 201763
7 201651
8 202046
9 201937
10 202126
11 202025
12 201519
13 201714
14 202313

About Jennifer Quantius

Jennifer Quantius is a scholar working on Pulmonary and Respiratory Medicine, Otorhinolaryngology, Artificial Intelligence, Immunology and Oncology, having authored 14 papers that have together received 951 indexed citations. Recurring topics across this work include Neonatal Respiratory Health Research (6 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), Head and Neck Cancer Studies (2 papers), AI in cancer detection (2 papers), Cancer Immunotherapy and Biomarkers (1 paper), Sarcoma Diagnosis and Treatment (1 paper), Immune cells in cancer (1 paper) and Influenza Virus Research Studies (1 paper). The work is most often cited by research in Pulmonary and Respiratory Medicine (587 citations), Hepatology (62 citations), Genetics (42 citations), Rehabilitation (25 citations) and Molecular Biology (221 citations). Jennifer Quantius has collaborated with scholars based in Germany, United States and China. Frequent co-authors include Susanne Herold, Savério Bellusci, Elie El Agha, Cho‐Ming Chao, Werner Seeger, Alena Moiseenko, Parviz Minoo, Denise Al Alam, Rory Edward Morty and BreAnne MacKenzie. Their work appears in journals such as Development, Clinical Cancer Research, Cell stem cell, American Journal of Physiology-Lung Cellular and Molecular Physiology and PLoS Pathogens.

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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