Natalie Shih

4.1k total citations · 2 hit papers
47 papers, 2.8k citations indexed

About

Natalie Shih is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Natalie Shih has authored 47 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 16 papers in Pulmonary and Respiratory Medicine and 16 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Natalie Shih's work include AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Prostate Cancer Diagnosis and Treatment (11 papers). Natalie Shih is often cited by papers focused on AI in cancer detection (19 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Prostate Cancer Diagnosis and Treatment (11 papers). Natalie Shih collaborates with scholars based in United States, Colombia and Netherlands. Natalie Shih's co-authors include Michael D. Feldman, Anant Madabhushi, John Tomaszewski, Ajay Basavanhally, Hannah Gilmore, Ángel Cruz-Roa, Fabio A. González, Shridar Ganesan, Zhi Wei and Sagarika Banerjee and has published in prestigious journals such as Journal of Clinical Investigation, Journal of Clinical Oncology and Blood.

In The Last Decade

Natalie Shih

46 papers receiving 2.7k 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.

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 →

Peers

Countries citing papers authored by Natalie Shih

Since Specialization

Citations

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

Fields of papers citing papers by Natalie Shih

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalie Shih

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

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Rare subclonal sequencing of breast cancers indicates putative metastatic driver mutations are predominately acquired after dissemination 2024 ·Genome Medicine ·(unknown), Tien-Chi Pan, Dhruv K. Pant, Natalie Shih, Yan Chen, George K. Belka, Michaël Feldman, Angela DeMichele, Lewis A. Chodosh	4
2	Exploiting the CD200-CD200R immune checkpoint axis in multiple myeloma to enhance CAR T-cell therapy 2023 ·Blood ·Yan Tang, Wei Liu, (unknown), Omar Johnson, Zainul S. Hasanali, (unknown), Alexander A. Shestov, Raymone Pajarillo, (unknown), Matthew Holmes, Liping Wang, Natalie Shih, Roddy S. O’Connor, Marco Ruella, Alfred L. Garfall, David Allman, Dan T. Vogl, Adam D. Cohen, Carl H. June, Neil C. Sheppard	9
3	244MO A phase II trial targeting disseminated dormant tumor cells with hydroxychloroquine, everolimus or the combination to prevent recurrent breast cancer (“CLEVER”) 2023 ·Annals of Oncology ·Angela DeMichele, Amy S. Clark, Lauren J. Bayne, K. Rohn, (unknown), Paul Wileyto, Lindsay R. Berry, Stephanie DeLuca, Jason E. Savage, Igor Makhlin, Tony Pan, Jewell Graves, George K. Belka, Jiu‐Yao Wang, Natalie Shih, Donald A. Berry, Anupma Nayak, M. Feldman, Lewis A. Chodosh	6
4	Prognostic correlations with the microbiome of breast cancer subtypes 2021 ·Cell Death and Disease ·Sagarika Banerjee, Zhi Wei, Tian Tian, Dipayan Bose, Natalie Shih, Michael D. Feldman, Thaer Khoury, (unknown), Erle S. Robertson	79
5	Genomic landscape of metastatic breast cancer identifies preferentially dysregulated pathways and targets 2020 ·Journal of Clinical Investigation ·(unknown), Tien-Chi Pan, Dhruv K. Pant, Natalie Shih, Yan Chen, (unknown), (unknown), David Lieberman, Jennifer J.D. Morrissette, (unknown), Noah Goodman, S. William Stavropoulos, Kara N. Maxwell, (unknown), George K. Belka, Michael D. Feldman, Angela DeMichele, Lewis A. Chodosh	79
6	Distinct Microbial Signatures Associated With Different Breast Cancer Types 2018 ·Frontiers in Microbiology ·Sagarika Banerjee, Tian Tian, Zhi Wei, Natalie Shih, Michael D. Feldman, (unknown), Angela DeMichele, James C. Alwine, Erle S. Robertson	218
7	Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings 2018 ·PLoS ONE ·(unknown), (unknown), Robin Elliott, (unknown), Natalie Shih, Michael D. Feldman, Phillip D. Stricker, Warick Delprado, (unknown), Maret Böhm, Anne-Maree Haynes, Lee Ponsky, Pingfu Fu, Pallavi Tiwari, Satish E. Viswanath, Anant Madabhushi	47
8	Microbial Signatures Associated with Oropharyngeal and Oral Squamous Cell Carcinomas 2017 ·Scientific Reports ·Sagarika Banerjee, Tian Tian, Zhi Wei, (unknown), Natalie Shih, Ara A. Chalian, Bert W. O’Malley, Gregory S. Weinstein, Michael D. Feldman, James C. Alwine, Erle S. Robertson	62
9	Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent breakdown → 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
10	AutoStitcher: An Automated Program for Efficient and Robust Reconstruction of Digitized Whole Histological Sections from Tissue Fragments 2016 ·Scientific Reports ·(unknown), Andrew Janowczyk, (unknown), Mirabela Rusu, Natalie Shih, Michael D. Feldman, Phillip D. Stricker, Warick Delprado, (unknown), Maret Böhm, Anne-Maree Haynes, Lee Ponsky, Satish E. Viswanath, Anant Madabhushi	8
11	Distinct microbiological signatures associated with triple negative breast cancer 2015 ·Scientific Reports ·Sagarika Banerjee, Zhi Wei, (unknown), (unknown), Natalie Shih, Michael D. Feldman, Timothy R. Rebbeck, James C. Alwine, Erle S. Robertson	94
12	Risk Factors for gyrA and parC Mutations in Pseudomonas aeruginosa 2015 ·Infection Control and Hospital Epidemiology ·Valerie Cluzet, Ebbing Lautenbach, Irving Nachamkin, Mark Cary, Neil O. Fishman, Natalie Shih, Knashawn H. Morales, Darren R. Linkin	1
13	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
14	Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging 2015 ·Radiology ·Geert Litjens, Robin Elliott, Natalie Shih, Michael D. Feldman, Thiele Kobus, Christina Hulsbergen‐van de Kaa, Jelle O. Barentsz, Henkjan Huisman, Anant Madabhushi	43
15	Histostitcher™: An informatics software platform for reconstructing whole-mount prostate histology using the extensible imaging platform framework 2014 ·Journal of Pathology Informatics ·Róbert Tóth, Natalie Shih, John E. Tomaszewski, Michael D. Feldman, Oliver Kutter, (unknown), (unknown), (unknown), Anant Madabhushi	16
16	Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX 2012 ·Journal of Pathology Informatics ·Ajay Basavanhally, Michael D. Feldman, Natalie Shih, Carolyn Mies, John Tomaszewski, Shridar Ganesan, Anant Madabhushi	45
17	Image microarrays (IMA): Digital pathology’s missing tool 2011 ·Journal of Pathology Informatics ·Jason Hipp, Jerome Cheng, Liron Pantanowitz, Stephen M. Hewitt, Yukako Yagi, James Monaco, Anant Madabhushi, Jaime Rodriguez‐Canales, Jeffrey C. Hanson, Sinchita Roy‐Chowdhuri, Armando Filie, Michael D. Feldman, John E. Tomaszewski, Natalie Shih, (unknown), Giuseppe Giaccone, Michael R. Emmert‐Buck, Ulysses J. Balis	8
18	Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI 2011 ·PubMed ·(unknown), Jonathan Chappelow, John Tomaszewski, Michael D. Feldman, Mark Rosen, Natalie Shih, Anant Madabhushi	18
19	HistoStitcher©: An interactive program for accurate and rapid reconstruction of digitized whole histological sections from tissue fragments 2011 ·Computerized Medical Imaging and Graphics ·Jonathan Chappelow, John E. Tomaszewski, Michael D. Feldman, Natalie Shih, Anant Madabhushi	31
20	Detection of prostate cancer on histopathology using color fractals and Probabilistic Pairwise Markov models 2011 ·PubMed ·Genong Yu, James Monaco, John Tomaszewski, Natalie Shih, Michael D. Feldman, Anant Madabhushi	15

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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