Ivan Lerner

582 total citations · 1 hit paper
13 papers, 240 citations indexed

About

Ivan Lerner is a scholar working on Artificial Intelligence, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Ivan Lerner has authored 13 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Molecular Biology and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Ivan Lerner's work include Biomedical Text Mining and Ontologies (5 papers), Topic Modeling (4 papers) and Machine Learning in Healthcare (3 papers). Ivan Lerner is often cited by papers focused on Biomedical Text Mining and Ontologies (5 papers), Topic Modeling (4 papers) and Machine Learning in Healthcare (3 papers). Ivan Lerner collaborates with scholars based in France, United States and Netherlands. Ivan Lerner's co-authors include Nicolás Paris, Antoine Neuraz, Anita Burgun, Bastien Rance, Xavier Tannier, Xavier Jouven, Jean‐Philippe Empana, Éloi Marijon, Frankie Beganton and Hanno L. Tan and has published in prestigious journals such as Bioinformatics, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Ivan Lerner

12 papers receiving 238 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Incidence of Sudden Cardiac Death in the European Union

2022 88 citations Jean‐Philippe Empana, Ivan Lerner et al. Journal of the American College of Cardiology profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ivan Lerner France	8	76	60	49	46	26	13	240
Le Zheng China	8	77 1.0×	33 0.6×	16 0.3×	27 0.6×	74 2.8×	12	291
Scott Pappada United States	9	46 0.6×	58 1.0×	19 0.4×	18 0.4×	26 1.0×	21	376
Sae Won Choi South Korea	10	42 0.6×	35 0.6×	17 0.3×	93 2.0×	35 1.3×	21	242
Jeffrey W. Pennington United States	9	33 0.4×	21 0.3×	68 1.4×	12 0.3×	65 2.5×	24	278
Alexander J. Ryu United States	9	17 0.2×	63 1.1×	30 0.6×	12 0.3×	22 0.8×	43	247
Xingzhi Sun China	8	85 1.1×	84 1.4×	25 0.5×	6 0.1×	39 1.5×	17	315
Oliver Wang United States	7	113 1.5×	78 1.3×	12 0.2×	15 0.3×	60 2.3×	13	363
Sreekar Mantena United States	10	48 0.6×	17 0.3×	50 1.0×	12 0.3×	25 1.0×	16	240
Nekane Larburu Spain	9	50 0.7×	81 1.4×	34 0.7×	9 0.2×	10 0.4×	29	236
Patricia Kovatch United States	8	82 1.1×	69 1.1×	25 0.5×	7 0.2×	32 1.2×	29	256

Countries citing papers authored by Ivan Lerner

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Lerner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Lerner

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

All Works

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13 of 13 papers shown

1.

Neuraz, Antoine, Thibaut Fabacher, Nicolas Garcelon, et al.. (2024). Facilitating phenotyping from clinical texts: the medkit library. Bioinformatics. 40(12). 1 indexed citations

2.

Neuraz, Antoine, et al.. (2024). TAXN: Translate Align Extract Normalize, a Multilingual Extraction Tool for Clinical Texts. Studies in health technology and informatics. 310. 649–653. 1 indexed citations

3.

Mansuet‐Lupo, Audrey, Hélène Blons, Elizabeth Fabre, et al.. (2024). Clinical and molecular characteristics associated with high PD-L1 expression in EGFR-mutated lung adenocarcinoma. PLoS ONE. 19(11). e0307161–e0307161. 1 indexed citations

4.

Empana, Jean‐Philippe, Ivan Lerner, Marie‐Cécile Perier, et al.. (2022). Ultrasensitive Troponin I and Incident Cardiovascular Disease. Arteriosclerosis Thrombosis and Vascular Biology. 42(12). 1471–1481. 10 indexed citations

5.

Lerner, Ivan, et al.. (2022). Machine-learning-derived sepsis bundle of care. Intensive Care Medicine. 49(1). 26–36. 15 indexed citations

6.

Empana, Jean‐Philippe, Ivan Lerner, Fredrik Folke, et al.. (2022). Incidence of Sudden Cardiac Death in the European Union. Journal of the American College of Cardiology. 79(18). 1818–1827. 88 indexed citations breakdown →

7.

Lerner, Ivan, Arnaud Serret-Larmande, Bastien Rance, et al.. (2022). Mining Electronic Health Records for Drugs Associated With 28-day Mortality in COVID-19: Pharmacopoeia-wide Association Study (PharmWAS). JMIR Medical Informatics. 10(3). e35190–e35190. 2 indexed citations

8.

Vincent, Marc, et al.. (2022). Using Deep Learning to Improve Phenotyping from Clinical Reports. Studies in health technology and informatics. 290. 282–286. 7 indexed citations

9.

Feldman, Sarah, et al.. (2021). Hybrid Deep Learning for Medication-Related Information Extraction From Clinical Texts in French: MedExt Algorithm Development Study. JMIR Medical Informatics. 9(3). e17934–e17934. 20 indexed citations

10.

Neuraz, Antoine, Ivan Lerner, Nicolás Paris, et al.. (2020). Natural Language Processing for Rapid Response to Emergent Diseases: Case Study of Calcium Channel Blockers and Hypertension in the COVID-19 Pandemic. Journal of Medical Internet Research. 22(8). e20773–e20773. 52 indexed citations

11.

Bataille, Pierre, Aurélien Amiot, Pascal Claudepierre, et al.. (2020). Infection à SARS-CoV-2 et biomédicaments : étude multicentrique française de 7808 patients. Annales de Dermatologie et de Vénéréologie. 147(12). A127–A128.

12.

Lerner, Ivan, Nicolás Paris, & Xavier Tannier. (2019). Terminologies augmented recurrent neural network model for clinical\n named entity recognition. arXiv (Cornell University). 25 indexed citations

13.

Lerner, Ivan, Perrine Créquit, Philippe Ravaud, & Ignacio Atal. (2018). Automatic screening using word embeddings achieved high sensitivity and workload reduction for updating living network meta-analyses. Journal of Clinical Epidemiology. 108. 86–94. 18 indexed citations

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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