Matthew Brendel

2.4k total citations
19 papers, 410 citations indexed

About

Matthew Brendel is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Matthew Brendel has authored 19 papers receiving a total of 410 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 5 papers in Oncology and 5 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Matthew Brendel's work include Radiomics and Machine Learning in Medical Imaging (3 papers), Molecular Biology Techniques and Applications (3 papers) and Reproductive Biology and Fertility (2 papers). Matthew Brendel is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (3 papers), Molecular Biology Techniques and Applications (3 papers) and Reproductive Biology and Fertility (2 papers). Matthew Brendel collaborates with scholars based in United States, Israel and China. Matthew Brendel's co-authors include Olivier Elemento, Mateusz M. Urbanski, Carmen V. Melendez‐Vasquez, Fei Wang, Alexandros Sigaras, Iman Hajirasouliha, Pegah Khosravi, Pantelis Zisimopoulos, J. Wesley Barnes and Chang Su and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and The Journal of Cell Biology.

In The Last Decade

Matthew Brendel

17 papers receiving 400 citations

Peers

Matthew Brendel

RNMI

PRM

Zahra Saadatpour Iran

Tingfeng Chen China

Minki Kim South Korea

Shann-Ching Chen United States

Zachary Englander United States

Hannah Horng United States

Jeffrey L. Clendenon United States

Li-Ying Feng China

Linda Ly Australia

Mika Kaakinen Finland

Zahra Saadatpour Iran

Matthew Brendel

240 ×1.9

111 ×1.2

RNMI

69 ×0.9

56 ×0.9

41 ×0.7

PRM

Citations per year, relative to Matthew Brendel Matthew Brendel (= 1×) peers Zahra Saadatpour

Countries citing papers authored by Matthew Brendel

Since Specialization

Citations

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

Fields of papers citing papers by Matthew Brendel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Brendel

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

All Works

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19 of 19 papers shown

Osman, Mohamed, Matthew Brendel, Catherine M. Tangen, et al.. (2025). Predicting response to neoadjuvant chemotherapy in muscle-invasive bladder cancer via interpretable multimodal deep learning. npj Digital Medicine. 8(1). 174–174. 6 indexed citations

Rajendran, Suraj, Matthew Brendel, J. Wesley Barnes, et al.. (2024). Automatic ploidy prediction and quality assessment of human blastocysts using time-lapse imaging. Nature Communications. 15(1). 7756–7756. 10 indexed citations

Rajendran, Suraj, Matthew Brendel, J. Wesley Barnes, et al.. (2024). Automatic Ploidy Prediction and Quality Assessment of Human Blastocysts Using Time-Lapse Imaging. Obstetrical & Gynecological Survey. 79(12). 725–726.

Faltas, Bishoy M., Mohamed Osman, Matthew Brendel, et al.. (2024). Predicting clinical outcomes in the S1314-COXEN trial using a multimodal deep learning model integrating histopathology, cell types, and gene expression.. Journal of Clinical Oncology. 42(4_suppl). 533–533.

Brendel, Matthew, Michael Sigouros, Alexandros Sigaras, et al.. (2022). Weakly-supervised tumor purity prediction from frozen H&E stained slides. EBioMedicine. 80. 104067–104067. 14 indexed citations

Barnes, J. Wesley, Matthew Brendel, Vianne R. Gao, et al.. (2022). A non-invasive artificial intelligence approach for the prediction of human blastocyst ploidy: a retrospective model development and validation study. The Lancet Digital Health. 5(1). e28–e40. 65 indexed citations

Li, Ying, Matthew Brendel, Ning Wu, et al.. (2022). Machine learning models for identifying predictors of clinical outcomes with first-line immune checkpoint inhibitor therapy in advanced non-small cell lung cancer. Scientific Reports. 12(1). 17670–17670. 6 indexed citations

Konnaris, Maxwell A., Matthew Brendel, Mark Alan Fontana, et al.. (2022). Computational pathology for musculoskeletal conditions using machine learning: advances, trends, and challenges. Arthritis Research & Therapy. 24(1). 68–68. 10 indexed citations

Brendel, Matthew, et al.. (2022). Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review. Genomics Proteomics & Bioinformatics. 20(5). 814–835. 47 indexed citations

10.

Wong, Sam, Simone Alidori, David Ulmert, et al.. (2021). Fibrillar pharmacology of functionalized nanocellulose. Scientific Reports. 11(1). 157–157. 9 indexed citations

11.

Brendel, Matthew, Mingquan Lin, Qingyu Chen, et al.. (2021). Multi-task deep learning-based survival analysis on the prognosis of late AMD using the longitudinal data in AREDS.. PubMed. 2021. 506–515. 4 indexed citations

12.

Khosravi, Pegah, Mahmoud Eljalby, Ehsan Kazemi, et al.. (2021). A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion. Journal of Magnetic Resonance Imaging. 54(2). 462–471. 82 indexed citations

13.

Brendel, Matthew, Chang Su, Yu Hou, Claire Henchcliffe, & Fei Wang. (2021). Comprehensive subtyping of Parkinson’s disease patients with similarity fusion: a case study with BioFIND data. npj Parkinson s Disease. 7(1). 83–83. 7 indexed citations

14.

Jiang, Yang, Tai Wang, Lina Zhao, et al.. (2020). Gold/alpha-lactalbumin nanoprobes for the imaging and treatment of breast cancer. Nature Biomedical Engineering. 4(7). 686–703. 75 indexed citations

15.

Barros, Marilia, William J. Houlihan, Chelsea Paresi, et al.. (2020). γ-Secretase Partitioning into Lipid Bilayers Remodels Membrane Microdomains after Direct Insertion. Langmuir. 36(23). 6569–6579. 5 indexed citations

16.

Urbanski, Mateusz M., Matthew Brendel, & Carmen V. Melendez‐Vasquez. (2019). Acute and chronic demyelinated CNS lesions exhibit opposite elastic properties. Scientific Reports. 9(1). 999–999. 51 indexed citations

17.

Rosen, Jonathan N., et al.. (2019). The Drosophila Ninein homologue Bsg25D cooperates with Ensconsin in myonuclear positioning. The Journal of Cell Biology. 218(2). 524–540. 15 indexed citations

18.

Ricca, Jacob, Mesruh Turkekul, Afşar Barlas, et al.. (2017). Validation of Anti-Mouse PDL-1 Goat Polyclonal Antibody Staining with Mouse PDL-1 In Situ Hybridization on Adjacent Sections of Cell Pellets and Mouse Tumors. Methods in molecular biology. 1554. 253–262. 1 indexed citations

19.

Turkekul, Mesruh, Afşar Barlas, Dmitry Yarilin, et al.. (2017). Automated Double In Situ Detection of Mouse Lgr5 mRNA and Lysozyme Protein in Examining the Neighboring Cell Types of the Mouse Intestinal Crypt. Methods in molecular biology. 1554. 263–272. 3 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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