Travis Zack

28.7k total citations · 3 hit papers
27 papers, 3.4k citations indexed

About

Travis Zack is a scholar working on Artificial Intelligence, Health Informatics and Molecular Biology. According to data from OpenAlex, Travis Zack has authored 27 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 8 papers in Health Informatics and 7 papers in Molecular Biology. Recurrent topics in Travis Zack's work include Artificial Intelligence in Healthcare and Education (8 papers), Machine Learning in Healthcare (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Travis Zack is often cited by papers focused on Artificial Intelligence in Healthcare and Education (8 papers), Machine Learning in Healthcare (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Travis Zack collaborates with scholars based in United States, Canada and United Kingdom. Travis Zack's co-authors include Rameen Beroukhim, Scott L. Carter, Gad Getz, Hui Shen, Peter W. Laird, Matthew Meyerson, Steven E. Schumacher, Barbara A. Weir, Stacey Gabriel and Eric S. Lander and has published in prestigious journals such as Nature, Cell and Nature Medicine.

In The Last Decade

Travis Zack

26 papers receiving 3.4k 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.

Pan-cancer patterns of somatic copy number alteration

2013 1.2k citations Travis Zack, Steven E. Schumacher et al. Nature Genetics profile →
Absolute quantification of somatic DNA alterations in human cancer

2012 1.1k citations Scott L. Carter, Hui Shen et al. profile →
Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study

2023 222 citations Travis Zack, Eric Lehman et al. The Lancet Digital Health profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Travis Zack United States	13	1.9k	1.6k	719	541	501	27	3.4k
Stephen Yip Canada	30	1.0k 0.5×	655 0.4×	565 0.8×	178 0.3×	757 1.5×	150	2.8k
Karin A. Oien United Kingdom	31	1.1k 0.6×	834 0.5×	2.1k 2.9×	119 0.2×	496 1.0×	64	3.6k
Farid Moinfar Austria	31	925 0.5×	1.1k 0.7×	955 1.3×	325 0.6×	510 1.0×	80	3.1k
David N. Church United Kingdom	28	1.1k 0.6×	1.3k 0.8×	1.7k 2.3×	218 0.4×	687 1.4×	75	4.4k
Valsamo Anagnostou United States	31	1.7k 0.9×	1.0k 0.6×	2.2k 3.1×	279 0.5×	1.2k 2.5×	112	4.4k
C. Benedikt Westphalen Germany	30	1.4k 0.7×	1.2k 0.8×	3.0k 4.2×	307 0.6×	733 1.5×	132	4.8k
Caterina Marchiò Italy	42	2.2k 1.2×	2.4k 1.5×	2.9k 4.0×	486 0.9×	984 2.0×	163	5.8k
Blaise Clarke Canada	44	1.6k 0.9×	1.0k 0.6×	1.5k 2.1×	305 0.6×	648 1.3×	162	5.1k
Pierre O. Chappuis Switzerland	31	1.3k 0.7×	1.5k 0.9×	1.7k 2.4×	1.4k 2.6×	384 0.8×	107	3.6k

Countries citing papers authored by Travis Zack

Since Specialization

Citations

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

Fields of papers citing papers by Travis Zack

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Travis Zack

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Miao, Brenda Y., Irene Y. Chen, Christopher Y. K. Williams, et al.. (2025). The MI-CLAIM-GEN checklist for generative artificial intelligence in health. Nature Medicine. 31(5). 1394–1398. 7 indexed citations

Sushil, Madhumita, et al.. (2024). A comparative study of large language model-based zero-shot inference and task-specific supervised classification of breast cancer pathology reports. Journal of the American Medical Informatics Association. 31(10). 2315–2327. 21 indexed citations

Hong, Julian C., et al.. (2024). Large language models to evaluate racial discrepancies in performance status assignment.. Journal of Clinical Oncology. 42(16_suppl). 1561–1561. 1 indexed citations

Doernberg, Sarah B., et al.. (2024). Predictive Modeling of Drug‐Related Adverse Events with Real‐World Data: A Case Study of Linezolid Hematologic Outcomes. Clinical Pharmacology & Therapeutics. 115(4). 847–859. 3 indexed citations

Zack, Travis, Madhumita Sushil, Brenda Y. Miao, et al.. (2024). Assessing Large Language Models for Oncology Data Inference From Radiology Reports. JCO Clinical Cancer Informatics. 8(8). e2400126–e2400126. 4 indexed citations

Chao, Hui, Travis Zack, & Andrew D. Leavitt. (2024). Screening Characteristics of Hemoglobin and Mean Corpuscular Volume for Detection of Iron Deficiency in Pregnancy. Obstetrics and Gynecology. 145(1). 91–94. 3 indexed citations

Spiegel, Daphna Y., William Zhang, Travis Zack, et al.. (2024). Exploring the Social Media Discussion of Breast Cancer Treatment Choices: Quantitative Natural Language Processing Study. JMIR Cancer. 11. e52886–e52886. 1 indexed citations

Zack, Travis, Madhumita Sushil, Brenda Y. Miao, et al.. (2024). Abstract B074: Clinical inference of location and trajectory of pancreatic cancer from radiology reports using zero-shot LLM. Cancer Research. 84(2_Supplement). B074–B074. 1 indexed citations

Sushil, Madhumita, et al.. (2024). CORAL: Expert-Curated Oncology Reports to Advance Language Model Inference. NEJM AI. 1(4). 30 indexed citations

10.

Zack, Travis, Eric Lehman, Mirac Süzgün, et al.. (2023). Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study. The Lancet Digital Health. 6(1). e12–e22. 222 indexed citations breakdown →

11.

Zack, Travis, Jennifer Wild, Amin Yaqubie, et al.. (2023). Defining incidence and complications of fibrolamellar liver cancer through tiered computational analysis of clinical data. npj Precision Oncology. 7(1). 29–29. 5 indexed citations

12.

Zack, Travis, et al.. (2022). A Clinical Reasoning-Encoded Case Library Developed through Natural Language Processing. Journal of General Internal Medicine. 38(1). 5–11. 4 indexed citations

13.

Jaimes, Camilo, Sridhar Vajapeyam, Douglas L. Brown, et al.. (2020). MR Imaging Correlates for Molecular and Mutational Analyses in Children with Diffuse Intrinsic Pontine Glioma. American Journal of Neuroradiology. 41(5). 874–881. 13 indexed citations

14.

Gurry, Thomas, Paul H. Dannenberg, Samuel G. Finlayson, et al.. (2018). Predictability and persistence of prebiotic dietary supplementation in a healthy human cohort. Scientific Reports. 8(1). 12699–12699. 34 indexed citations

15.

Taylor‐Weiner, Amaro, Travis Zack, Elizabeth O’Donnell, et al.. (2016). Genomic evolution and chemoresistance in germ-cell tumours. Nature. 540(7631). 114–118. 114 indexed citations

16.

Gong, Yongxing, Travis Zack, Luc G.T. Morris, et al.. (2014). Pan-cancer genetic analysis identifies PARK2 as a master regulator of G1/S cyclins. Nature Genetics. 46(6). 588–594. 134 indexed citations

17.

Hamilton, Mark P., Kimal Rajapakshe, Sean M. Hartig, et al.. (2013). Identification of a pan-cancer oncogenic microRNA superfamily anchored by a central core seed motif. Nature Communications. 4(1). 2730–2730. 91 indexed citations

18.

Zack, Travis, Steven E. Schumacher, Scott L. Carter, et al.. (2013). Pan-cancer patterns of somatic copy number alteration. Nature Genetics. 45(10). 1134–1140. 1243 indexed citations breakdown →

19.

Nijhawan, Deepak, Travis Zack, Yin Ren, et al.. (2012). Cancer Vulnerabilities Unveiled by Genomic Loss. Cell. 150(4). 842–854. 161 indexed citations

20.

Shao, Diane D., Aviad Tsherniak, Shuba Gopal, et al.. (2012). ATARiS: Computational quantification of gene suppression phenotypes from multisample RNAi screens. Genome Research. 23(4). 665–678. 78 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.

Explore authors with similar magnitude of impact