Hannah Gilmore

8.1k citations

78 papers · 5.4k indexed · 6 hit papers · h-index 33

Artificial Intelligence top 0.5%
Radiology, Nuclear Medicine and Imaging top 0.5%
Oncology top 2%
Molecular Biology top 10%
Computer Vision and Pattern Recognition top 1%

Co-authors: Anant MadabhushiJun XuMichael D. Feldman John Tomaszewski Natalie Shih Ajay Basavanhally Ángel Cruz-Roa Fabio A. González
Topics: AI in cancer detection (22 papers)Breast Cancer Treatment Studies (21 papers)Radiomics and Machine Learning in Medical Imaging (18 papers)
Cited by: Radiology, Nuclear Medicine and Imaging Health Informatics Artificial Intelligence
Journals: Proceedings of the National Academy of Sciences Journal of Clinical OncologySHILAP Revista de lepidopterología
Partner nations: United States Colombia China

In The Last Decade

Hannah Gilmore

75 papers receiving 5.3k citations

Hit Papers

5 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.

Stacked Sparse Autoencoder (SSAE) for Nuclei Detection on Breast Cancer Histopathology Images

2015 625 citations Jun Xu, Hannah Gilmore et al. profile →
Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI

2017 479 citations Nathaniel Braman, Maryam Etesami et al. Breast Cancer Research profile →
Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks

2014 377 citations Ángel Cruz-Roa, Ajay Basavanhally et al. profile →
Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent

2017 349 citations Ángel Cruz-Roa, Hannah Gilmore et al. Scientific Reports profile →
A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images

2016 337 citations Jun Xu, Hannah Gilmore et al. profile →
Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy forHER2 (ERBB2)–Positive Breast Cancer

2019 235 citations Nathaniel Braman, Prateek Prasanna et al. JAMA Network Open profile →

Peers

Countries citing papers authored by Hannah Gilmore

Since Specialization

Citations

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

Fields of papers citing papers by Hannah Gilmore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hannah Gilmore

This figure shows the co-authorship network connecting the top 25 collaborators of Hannah Gilmore. A scholar is included among the top collaborators of Hannah Gilmore 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 Hannah Gilmore. Hannah Gilmore 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

#	Work	Indexed citations
1	Epigenetic aging differentially impacts breast cancer risk by self-reported race 2024 ·PLoS ONE ·(unknown),Megan E. Miller,Hannah Gilmore,Cheryl L. Thompson,Fredrick R. Schumacher	1
2	Evaluating Dual-Targeted ECO/siRNA Nanoparticles against an Oncogenic lncRNA for Triple Negative Breast Cancer Therapy with Magnetic Resonance Molecular Imaging 2023 ·SHILAP Revista de lepidopterología ·(unknown),(unknown),Jiyoon Kim,Da Sun,Ryan Hall,Songqi Gao,Hannah Gilmore,William P. Schiemann,Zheng‐Rong Lu	18
3	Solitary Fibrous Tumor of Breast and Axilla: Clinicopathological Profile of Five Tumors With Comparison of Risk Stratification Models 2023 ·International Journal of Surgical Pathology ·Raza S. Hoda,(unknown),Hannah Gilmore,Xiaoyan Cui,Patrick J. McIntire,Andrew P. Sciallis,John S. Van Arnam,(unknown),J. Jordi Rowe,(unknown),Elizabeth M. Azzato,John R. Goldblum,Karen Fritchie,(unknown)	1
4	Magnetic resonance molecular imaging of extradomain B fibronectin enables detection of pancreatic ductal adenocarcinoma metastasis 2021 ·Magnetic Resonance Imaging ·Peter Qiao,(unknown),Yiqiao Liu,(unknown),Ryan Hall,Amita Vaidya,Hannah Gilmore,(unknown),(unknown),Debashish Roy,David L. Wilson,Zheng‐Rong Lu	16
5	Collagen fiber orientation disorder from H&E images is prognostic for early stage breast cancer: clinical trial validation 2021 ·npj Breast Cancer ·(unknown),Kaustav Bera,Paula Toro,Pingfu Fu,Zelin Zhang,Cheng Lu,Michael D. Feldman,Shridar Ganesan,Lori J. Goldstein,Nancy E. Davidson,Akisha Glasgow,Aparna Harbhajanka,Hannah Gilmore,Anant Madabhushi	44
6	Molecular Detection of SARS-CoV-2 Infection in FFPE Samples and Histopathologic Findings in Fatal SARS-CoV-2 Cases 2020 ·American Journal of Clinical Pathology ·Miroslav Sekulic,Holly Harper,Behtash Ghazi Nezami,(unknown),(unknown),(unknown),Clifford V. Harding,Hannah Gilmore,Navid Sadri	68
7	Concordance of breast cancer biomarker status between routine immunohistochemistry/in situ hybridization and Oncotype DX qRT-PCR with investigation of discordance, a study of 591 cases 2020 ·Human Pathology ·(unknown),Akisha Glasgow,(unknown),Hannah Gilmore,Aparna Harbhajanka	1
8	Clinicopathological and radiological characterization of myofibroblastoma of breast: A single institutional case review 2020 ·Annals of Diagnostic Pathology ·Mingfei Yan,(unknown),Hannah Gilmore,(unknown),(unknown),Aparna Harbhajanka	13
9	Systemic Delivery of Tumor-Targeting siRNA Nanoparticles against an Oncogenic LncRNA Facilitates Effective Triple-Negative Breast Cancer Therapy 2019 ·Bioconjugate Chemistry ·Amita Vaidya,Zhanhu Sun,Nadia Ayat,(unknown),Xujie Liu,(unknown),Da Sun,(unknown),(unknown),Siyuan He,Hannah Gilmore,William P. Schiemann,Zheng‐Rong Lu	142
10	Association of Peritumoral Radiomics With Tumor Biology and Pathologic Response to Preoperative Targeted Therapy forHER2 (ERBB2)–Positive Breast Cancerbreakdown → 2019 ·JAMA Network Open ·Nathaniel Braman,Prateek Prasanna,Jon Whitney,Salendra Singh,Niha Beig,Maryam Etesami,‬David D. B. Bates,Katherine Gallagher,B Bloch,Manasa Vulchi,Paulette Turk,Kaustav Bera,Jame Abraham,William M. Sikov,George Somlo,Lyndsay N. Harris,Hannah Gilmore,Donna Plecha,Vinay Varadan,Anant Madabhushi	235
11	Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRIbreakdown → 2017 ·Breast Cancer Research ·Nathaniel Braman,Maryam Etesami,Prateek Prasanna,Christina Dubchuk,Hannah Gilmore,Pallavi Tiwari,Donna Plecha,Anant Madabhushi	479
12	A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers 2017 ·Cytometry Part A ·David Romo‐Bucheli,Andrew Janowczyk,Hannah Gilmore,Eduardo Romero,Anant Madabhushi	46
13	Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extentbreakdown → 2017 ·Scientific Reports ·Ángel Cruz-Roa,Hannah Gilmore,Ajay Basavanhally,Michael D. Feldman,Shridar Ganesan,Natalie Shih,John Tomaszewski,Fabio A. González,Anant Madabhushi	349
14	Immune Signatures Following Single Dose Trastuzumab Predict Pathologic Response to PreoperativeTrastuzumab and Chemotherapy in HER2-Positive Early Breast Cancer 2016 ·Clinical Cancer Research ·Vinay Varadan,Hannah Gilmore,Kristy Miskimen,David Tuck,(unknown),Amad Awadallah,Ian E. Krop,Eric P. Winer,Veerle Bossuyt,George Somlo,Maysa Abu‐Khalaf,Mary Anne Fenton,William M. Sikov,Lyndsay N. Harris	75
15	Brief‐exposure to preoperative bevacizumab reveals a TGF‐β signature predictive of response in HER2‐negative breast cancers 2015 ·International Journal of Cancer ·Vinay Varadan,Sitharthan Kamalakaran,Hannah Gilmore,Nilanjana Banerjee,Angel Janevski,Kristy Miskimen,Nicole Williams,(unknown),Anant Madabhushi,Kimberly Lezon-Geyda,Veerle Bossuyt,Donald R. Lannin,Maysa Abu‐Khalaf,William M. Sikov,Nevenka Dimitrova,Lyndsay N. Harris	14
16	Optimizing sparse sequencing of single cells for highly multiplex copy number profiling 2015 ·Genome Research ·Timour Baslan,Jude Kendall,Brian Ward,Hilary Cox,Anthony Leotta,Linda Rodgers,M Riggs,(unknown),Guoli Sun,Yong Mao,Kristy Miskimen,Hannah Gilmore,Michael Saborowski,Nevenka Dimitrova,Alexander Krasnitz,Lyndsay N. Harris,Michael Wigler,James Hicks	86
17	Sparse Non-negative Matrix Factorization (SNMF) based color unmixing for breast histopathological image analysis 2015 ·Computerized Medical Imaging and Graphics ·Jun Xu,Lei Xiang,(unknown),Shridar Ganesan,Michael D. Feldman,Natalie Shih,Hannah Gilmore,Anant Madabhushi	48
18	MUC1 is expressed at high frequency in early-stage basal-like triple-negative breast cancer 2013 ·Human Pathology ·Alan Siroy,Fadi W. Abdul‐Karim,John D. Miedler,(unknown),Pingfu Fu,Hannah Gilmore,Joseph Baar	72
19	Defining the cellular precursors to human breast cancer 2011 ·Proceedings of the National Academy of Sciences ·Patricia J. Keller,Lisa M. Arendt,Adam Skibinski,Tanya Logvinenko,Ina Klebba,Shumin Dong,Avi Smith,Aleix Prat,Charles M. Perou,Hannah Gilmore,Stuart J. Schnitt,Stephen P. Naber,Jonathan A. Garlick,Charlotte Kuperwasser	160
20	Genetic Predisposition Directs Breast Cancer Phenotype by Dictating Progenitor Cell Fate 2011 ·Cell stem cell ·Theresa A. Proia,Patricia J. Keller,Piyush B. Gupta,Ina Klebba,(unknown),Maja Sedic,Hannah Gilmore,Nadine Tung,Stephen P. Naber,Stuart J. Schnitt,Eric S. Lander,Charlotte Kuperwasser	284

About Hannah Gilmore

Hannah Gilmore is a scholar working on Cancer Research, Dermatology and Pathology and Forensic Medicine, having authored 78 papers that have together received 5.4k indexed citations. Recurring topics across this work include AI in cancer detection (22 papers), Breast Cancer Treatment Studies (21 papers) and Radiomics and Machine Learning in Medical Imaging (18 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.3k citations), Health Informatics (118 citations) and Artificial Intelligence (2.3k citations). Hannah Gilmore has collaborated with scholars based in United States, Colombia and China. Frequent co-authors include Anant Madabhushi, Jun Xu, Michael D. Feldman, John Tomaszewski, Natalie Shih, Ajay Basavanhally, Ángel Cruz-Roa, Fabio A. González, Shridar Ganesan and Andrew Janowczyk. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

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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