Robert Tinn

2.4k total citations · 1 hit paper
5 papers, 1.1k citations indexed

About

Robert Tinn is a scholar working on Artificial Intelligence, Molecular Biology and Health Informatics. According to data from OpenAlex, Robert Tinn has authored 5 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 3 papers in Molecular Biology and 1 paper in Health Informatics. Recurrent topics in Robert Tinn's work include Biomedical Text Mining and Ontologies (3 papers), Topic Modeling (3 papers) and Machine Learning in Healthcare (2 papers). Robert Tinn is often cited by papers focused on Biomedical Text Mining and Ontologies (3 papers), Topic Modeling (3 papers) and Machine Learning in Healthcare (2 papers). Robert Tinn collaborates with scholars based in United States. Robert Tinn's co-authors include Hoifung Poon, Naoto Usuyama, 裕二池谷, Tristan Naumann, Jianfeng Gao, Hao Cheng, Michael Lucas, Xiaodong Liu, Xiaodong Liu and Shruthi Bannur and has published in prestigious journals such as Journal of Clinical Oncology, Patterns and arXiv (Cornell University).

In The Last Decade

Robert Tinn

5 papers receiving 1.1k 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.

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

2021 1.0k citations 裕二池谷, Robert Tinn et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Robert Tinn United States	4	840	483	166	105	71	5	1.1k
Naoto Usuyama United States	7	867 1.0×	500 1.0×	175 1.1×	124 1.2×	88 1.2×	14	1.2k
裕二池谷 United States	10	948 1.1×	534 1.1×	175 1.1×	122 1.2×	90 1.3×	19	1.3k
Michael Lucas Australia	4	790 0.9×	456 0.9×	146 0.9×	91 0.9×	68 1.0×	14	1.1k
Qiao Jin United States	16	647 0.8×	273 0.6×	328 2.0×	131 1.2×	78 1.1×	51	1.2k
William Boag United States	6	715 0.9×	301 0.6×	99 0.6×	83 0.8×	52 0.7×	12	873
Asma Ben Abacha United States	20	1.0k 1.2×	418 0.9×	98 0.6×	69 0.7×	257 3.6×	51	1.3k
Aurélie Névéol France	19	944 1.1×	809 1.7×	75 0.5×	71 0.7×	27 0.4×	71	1.4k
Renqian Luo China	7	408 0.5×	157 0.3×	144 0.9×	72 0.7×	58 0.8×	10	799
Po‐Ting Lai Taiwan	13	394 0.5×	378 0.8×	98 0.6×	36 0.3×	22 0.3×	39	676
Lana Yeganova United States	12	367 0.4×	313 0.6×	88 0.5×	33 0.3×	20 0.3×	38	596

Countries citing papers authored by Robert Tinn

Since Specialization

Citations

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

Fields of papers citing papers by Robert Tinn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robert Tinn

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

All Works

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5 of 5 papers shown

1.

Tinn, Robert, Hao Cheng, 裕二池谷, et al.. (2023). Fine-tuning large neural language models for biomedical natural language processing. Patterns. 4(4). 100729–100729. 72 indexed citations

2.

Liu, Qianchu, Stephanie L. Hyland, Shruthi Bannur, et al.. (2023). Exploring the Boundaries of GPT-4 in Radiology. 14414–14445. 14 indexed citations

3.

Mu, Wei, Rajesh C. Rao, Robert Tinn, et al.. (2023). Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. Patterns. 4(4). 100726–100726. 15 indexed citations

4.

Piening, Brian, Bela Bapat, Roshanthi Weerasinghe, et al.. (2023). Improved outcomes from reflex comprehensive genomic profiling-guided precision therapeutic selection across a major US healthcare system.. Journal of Clinical Oncology. 41(16_suppl). 6622–6622. 2 indexed citations

5.

池谷, 裕二, Robert Tinn, Hao Cheng, et al.. (2021). Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. arXiv (Cornell University). 3(1). 1–23. 1027 indexed citations breakdown →

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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