Kate Lillard

624 total citations
7 papers, 390 citations indexed

About

Kate Lillard is a scholar working on Oncology, Surgery and Molecular Biology. According to data from OpenAlex, Kate Lillard has authored 7 papers receiving a total of 390 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 2 papers in Surgery and 2 papers in Molecular Biology. Recurrent topics in Kate Lillard's work include Radiomics and Machine Learning in Medical Imaging (2 papers), Immune cells in cancer (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). Kate Lillard is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), Immune cells in cancer (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). Kate Lillard collaborates with scholars based in Japan, United Kingdom and United States. Kate Lillard's co-authors include Hideki Ueno, Ines P. Nearchou, David J. Harrison, Peter D. Caie, Giovanni Lujan, Anil V. Parwani, Douglas Bowman, Oliver C. Turner, Ana Yuil‐Valdes and Douglas J. Hartman and has published in prestigious journals such as Cancers, Histopathology and Cancer Immunology Research.

In The Last Decade

Kate Lillard

7 papers receiving 376 citations

Peers

Kate Lillard
Vipul Baxi United States
Saba Shafi United States
Nathan Ing United States
Quirine F. Manson Netherlands
Benoît Plancoulaine France
Justinas Besusparis Lithuania
Nicole B. Johnson United States
Alexander W. Jung United Kingdom
Marcory van Dijk Netherlands
Peter Ntiamoah United States
Vipul Baxi United States
Kate Lillard
Citations per year, relative to Kate Lillard Kate Lillard (= 1×) peers Vipul Baxi

Countries citing papers authored by Kate Lillard

Since Specialization
Citations

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

Fields of papers citing papers by Kate Lillard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kate Lillard

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

All Works

7 of 7 papers shown
1.
Kouzu, Keita, Ines P. Nearchou, Yoshiki Kajiwara, et al.. (2022). Deep‐learning‐based classification of desmoplastic reaction on H&E predicts poor prognosis in oesophageal squamous cell carcinoma. Histopathology. 81(2). 255–263. 7 indexed citations
2.
Nearchou, Ines P., Hideki Ueno, Yoshiki Kajiwara, et al.. (2021). Automated Detection and Classification of Desmoplastic Reaction at the Colorectal Tumour Front Using Deep Learning. Cancers. 13(7). 1615–1615. 12 indexed citations
3.
Nearchou, Ines P., Kate Lillard, Yoshiki Kajiwara, et al.. (2020). Spatial immune profiling of the colorectal tumor microenvironment predicts good outcome in stage II patients. npj Digital Medicine. 3(1). 71–71. 43 indexed citations
4.
Nearchou, Ines P., et al.. (2019). Automated Analysis of Lymphocytic Infiltration, Tumor Budding, and Their Spatial Relationship Improves Prognostic Accuracy in Colorectal Cancer. Cancer Immunology Research. 7(4). 609–620. 68 indexed citations
5.
Aeffner, Famke, Mark D. Zarella, Marilyn M. Bui, et al.. (2019). Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association. Journal of Pathology Informatics. 10(1). 9–9. 242 indexed citations
6.
Lillard, Kate, et al.. (2011). Zebrafish Models of Germ Cell Tumor. Methods in cell biology. 105. 1–24. 16 indexed citations
7.
Potts, Steven J., et al.. (2009). P26: Performance of a novel automated microvessel analysis algorithm across whole slide digital images. Experimental and Toxicologic Pathology. 61(4). 413–413. 2 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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2026