Lauren Costa

1.1k total citations
12 papers, 190 citations indexed

About

Lauren Costa is a scholar working on Molecular Biology, Artificial Intelligence and Epidemiology. According to data from OpenAlex, Lauren Costa has authored 12 papers receiving a total of 190 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Artificial Intelligence and 3 papers in Epidemiology. Recurrent topics in Lauren Costa's work include Biomedical Text Mining and Ontologies (4 papers), Genetic Associations and Epidemiology (2 papers) and Chronic Disease Management Strategies (2 papers). Lauren Costa is often cited by papers focused on Biomedical Text Mining and Ontologies (4 papers), Genetic Associations and Epidemiology (2 papers) and Chronic Disease Management Strategies (2 papers). Lauren Costa collaborates with scholars based in United States, Australia and Mexico. Lauren Costa's co-authors include Kelly Cho, Yuk‐Lam Ho, David Gagnon, Peter W.F. Wilson, Ashley Galloway, J. Michael Gaziano, Bing Lü, Jane A. Driver, Jason L. Vassy and Ariela R. Orkaby and has published in prestigious journals such as Proceedings of the National Academy of Sciences, JAMA and Bioinformatics.

In The Last Decade

Lauren Costa

10 papers receiving 189 citations

Peers

Lauren Costa

SURGE

EE

EDM

CCM

MB

Joaquim Cristino United States

A Gray United Kingdom

Lisa Pennells United Kingdom

Hani Sabbour United Arab Emirates

Krzysztof Chlebus Poland

Beatriz Boned Spain

Ashley Galloway United States

Kenneth Quinto United States

Karl Richardson United States

Elisabet González-Lao Spain

Joaquim Cristino United States

Lauren Costa

118 ×1.3

SURGE

35 ×0.7

EE

46 ×1.1

EDM

89 ×2.4

CCM

34 ×1.3

MB

Citations per year, relative to Lauren Costa Lauren Costa (= 1×) peers Joaquim Cristino

Countries citing papers authored by Lauren Costa

Since Specialization

Citations

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

Fields of papers citing papers by Lauren Costa

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lauren Costa

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

All Works

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12 of 12 papers shown

1.

Ivey, Kerry L., et al.. (2025). Quantifying the impact of biobanks and cohort studies. Proceedings of the National Academy of Sciences. 122(16). e2427157122–e2427157122. 1 indexed citations

2.

Ho, Yuk‐Lam, Nicole Kosik, Kelly Harrington, et al.. (2024). Military and occupational exposures among Veterans in the Million Veteran Program by survey self-report: a descriptive study. Occupational and Environmental Medicine. 81(10). 522–528.

3.

Danciu, Ioana, Debangshu Mukherjee, Ian Goethert, et al.. (2024). VISION: Toward a Standardized Process for Radiology Image Management at the National Level. 2(8). 1–7.

4.

Wen, Jun, Xiang Zhang, Vidul Ayakulangara Panickan, et al.. (2023). Multimodal representation learning for predicting molecule–disease relations. Bioinformatics. 39(2). 12 indexed citations

5.

Wen, Jun, Jue Hou, Clara-Lea Bonzel, et al.. (2023). LATTE: Label-efficient incident phenotyping from longitudinal electronic health records. Patterns. 5(1). 100906–100906. 6 indexed citations

6.

Ferolito, Brian R., Ítalo Faria do Valle, Hanna Gerlovin, et al.. (2022). Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach. Scientific Reports. 12(1). 14914–14914. 3 indexed citations

7.

Valle, Ítalo Faria do, Brian R. Ferolito, Hanna Gerlovin, et al.. (2022). Network-medicine framework for studying disease trajectories in U.S. veterans. Scientific Reports. 12(1). 12018–12018. 9 indexed citations

8.

Link, Nicholas, Sicong Huang, Tianrun Cai, et al.. (2022). Binary acronym disambiguation in clinical notes from electronic health records with an application in computational phenotyping. International Journal of Medical Informatics. 162. 104753–104753. 8 indexed citations

9.

Tarko, Laura, Lauren Costa, Ashley Galloway, et al.. (2022). Racial and Ethnic Differences in Short- and Long-term Mortality by Stroke Type. Neurology. 98(24). e2465–e2473. 9 indexed citations

10.

Raghavan, Sridharan, Yuk‐Lam Ho, Jason L. Vassy, et al.. (2020). Optimizing Atherosclerotic Cardiovascular Disease Risk Estimation for Veterans With Diabetes Mellitus. Circulation Cardiovascular Quality and Outcomes. 13(9). e006528–e006528. 3 indexed citations

11.

Danciu, Ioana, George Ostrouchov, Kelly Cho, et al.. (2020). JSONize: A Scalable Machine Learning Pipeline to Model Medical Notes as Semi-structured Documents.. PubMed. 2020. 533–541. 1 indexed citations

12.

Orkaby, Ariela R., Jane A. Driver, Yuk‐Lam Ho, et al.. (2020). Association of Statin Use With All-Cause and Cardiovascular Mortality in US Veterans 75 Years and Older. JAMA. 324(1). 68–68. 138 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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