Uri Lerner

22 papers receiving 1.7k citations

Uri Lerner's Hit Papers

Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study 2023 · 213 citations
2130+3+6Years since publication250500750

Peers

Uri Lerner
Comparison fields: 5 of 137
  • Environmental Engineering 860
  • Health, Toxicology and Mutagenesis 666
  • Automotive Engineering 199
  • Atmospheric Science 224
  • Neurology 164
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Nana Wu China
Chia-Tai Chan Taiwan
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Hamdy K. Elminir Egypt
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Countries citing papers authored by Uri Lerner

Since Specialization
Citations

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

Fields of papers citing papers by Uri Lerner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?
Hit paper breakdown →
2016760
2
Long covid outcomes at one year after mild SARS-CoV-2 infection: nationwide cohort study
Hit paper breakdown →
2023213
3
Bayesian Fault Detection and Diagnosis in Dynamic Systems
2000186
4 2014175
5
Hybrid Bayesian Networks for Reasoning about Complex Systems
2002102
6 200148
7 201343
8
Monitoring a complex physical system using a hybrid dynamic bayes net
200241
9 202330
10 201923
11 201321
12 201519
13 202118
14 201316
15 201515
16 201313
17 202212
18 20208
19 20257
20 20004

About Uri Lerner

Uri Lerner is a scholar working on Artificial Intelligence, Health, Toxicology and Mutagenesis, Environmental Engineering, Control and Systems Engineering and Infectious Diseases, having authored 23 papers that have together received 1.8k indexed citations. Recurring topics across this work include Air Quality Monitoring and Forecasting (6 papers), Air Quality and Health Impacts (5 papers), Bayesian Modeling and Causal Inference (5 papers), Target Tracking and Data Fusion in Sensor Networks (3 papers), Fault Detection and Control Systems (3 papers), Atmospheric chemistry and aerosols (2 papers), COVID-19 and Mental Health (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Environmental Engineering (860 citations), Health, Toxicology and Mutagenesis (666 citations), Automotive Engineering (199 citations), Atmospheric Science (224 citations) and Neurology (164 citations). Uri Lerner has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Barak Fishbain, David M. Broday, Matthias Vogt, Franck René Dauge, Philipp Schneider, Núria Castell, Alena Bartoňová, Daphne Koller, Ronald Parr and Gautam Biswas. Their work appears in journals such as The Science of The Total Environment, Environment International, Eurosurveillance, Journal of the American Academy of Child & Adolescent Psychiatry and npj Digital Medicine.

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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