Jose Net

1.2k total citations · 2 hit papers
26 papers, 870 citations indexed

About

Jose Net is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research and Pathology and Forensic Medicine. According to data from OpenAlex, Jose Net has authored 26 papers receiving a total of 870 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Cancer Research and 8 papers in Pathology and Forensic Medicine. Recurrent topics in Jose Net's work include Breast Cancer Treatment Studies (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and MRI in cancer diagnosis (8 papers). Jose Net is often cited by papers focused on Breast Cancer Treatment Studies (10 papers), Radiomics and Machine Learning in Medical Imaging (9 papers) and MRI in cancer diagnosis (8 papers). Jose Net collaborates with scholars based in United States, Ukraine and Canada. Jose Net's co-authors include Elizabeth S. Burnside, Gary J. Whitman, Maryellen L. Giger, Elizabeth J. Sutton, Elizabeth A. Morris, Hui Li, Karen Drukker, Erich P. Huang, Suzanne D. Conzen and Yitan Zhu and has published in prestigious journals such as Cancer, Cancer Research and Radiology.

In The Last Decade

Jose Net

22 papers receiving 864 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.

MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays

2016 373 citations Hui Li, Yitan Zhu et al. Radiology profile →
Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

2016 287 citations Hui Li, Yitan Zhu et al. npj Breast Cancer profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jose Net United States	10	743	290	180	146	143	26	870
Xueyi Zheng China	9	418 0.6×	228 0.8×	98 0.5×	102 0.7×	110 0.8×	15	605
Chao You China	15	459 0.6×	152 0.5×	142 0.8×	107 0.7×	108 0.8×	44	607
Panagiotis Kapetas Austria	21	1.2k 1.6×	280 1.0×	206 1.1×	98 0.7×	187 1.3×	62	1.4k
Mirinae Seo South Korea	18	671 0.9×	265 0.9×	277 1.5×	220 1.5×	210 1.5×	44	1.1k
Hongna Tan China	14	432 0.6×	188 0.6×	146 0.8×	82 0.6×	103 0.7×	29	688
Brittany Z. Dashevsky United States	12	490 0.7×	150 0.5×	214 1.2×	151 1.0×	93 0.7×	30	668
Stefanie Weigel Germany	16	438 0.6×	227 0.8×	273 1.5×	388 2.7×	308 2.2×	52	985
Isabel Schobert Germany	9	410 0.6×	167 0.6×	89 0.5×	127 0.9×	99 0.7×	18	694
Elżbieta Łuczyńska Poland	13	294 0.4×	149 0.5×	101 0.6×	78 0.5×	315 2.2×	53	573

Countries citing papers authored by Jose Net

Since Specialization

Citations

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

Fields of papers citing papers by Jose Net

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jose Net

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

Net, Jose, et al.. (2025). Change in Indications and Outcomes for Stereotactic Biopsy Following Transition from Full Field Digital Mammography + Digital Breast Tomosynthesis to Full Field Synthetic Mammography + Digital Breast Tomosynthesis. Medical Sciences. 13(1). 29–29.

Kwon, Deukwoo, Wei Zhao, Tulay Koru‐Sengul, et al.. (2024). A Multi-institutional Analysis of Factors Influencing the Rate of Positive MRI Biopsy Among Women with Early-Stage Breast Cancer. Annals of Surgical Oncology. 31(5). 3141–3153.

Net, Jose, et al.. (2024). Optimizing the Patient Experience for Women With Disabilities in the Breast Imaging Clinic. Journal of Breast Imaging. 6(2). 183–191. 2 indexed citations

Yepes, Monica, et al.. (2024). Appropriate Use of Medical Interpreters in the Breast Imaging Clinic. Journal of Breast Imaging. 6(3). 296–303. 2 indexed citations

White, Amy, Jose Net, Susan B. Kesmodel, et al.. (2022). The Association of Preoperative Magnetic Resonance Imaging (MRI) With Surgical Management in Patients With Early-Stage Breast Cancer. Journal of Surgical Research. 280. 114–122. 2 indexed citations

Net, Jose, et al.. (2022). Kikuchi-Fujimoto-like lymphadenopathy following COVID-19 vaccine: diagnosis and management. BMJ Case Reports. 15(12). e252030–e252030. 6 indexed citations

Net, Jose, et al.. (2022). The Challenge of Digital Breast Tomosynthesis–Detected Architectural Distortion of the Breast: Inter-reader Variability and Imaging Characteristics That May Improve Positive Predictive Value. Journal of Breast Imaging. 4(3). 263–272. 2 indexed citations

Net, Jose, et al.. (2022). Culturally Competent Care in the Breast Imaging Clinic: Hispanic/Latino Patients. Journal of Breast Imaging. 5(2). 188–194. 2 indexed citations

Net, Jose, et al.. (2021). Ductal and lobular carcinoma in situ arising within an enlarging biopsy proven fibroadenoma. BMJ Case Reports. 14(1). e237017–e237017. 5 indexed citations

10.

Lehrer, Michael, Anindya Bhadra, Visweswaran Ravikumar, et al.. (2018). High-dimensional regression analysis links magnetic resonance imaging features and protein expression and signaling pathway alterations in breast invasive carcinoma. Oncoscience. 5(1-2). 39–48. 2 indexed citations

11.

Net, Jose, Gary J. Whitman, Elizabeth A. Morris, et al.. (2018). Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype. Current Problems in Diagnostic Radiology. 48(5). 467–472. 14 indexed citations

12.

Sutton, Elizabeth J., Erich P. Huang, Karen Drukker, et al.. (2017). Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes. European Radiology Experimental. 1(1). 22–22. 27 indexed citations

13.

Collado‐Mesa, Fernando, et al.. (2017). Primary neuroendocrine carcinoma of the breast: report of 2 cases and literature review. Radiology Case Reports. 12(1). 1–12. 9 indexed citations

14.

Collado‐Mesa, Fernando, et al.. (2017). Time Spent by Breast Imaging Radiologists to Perform Value-Added Activities at an Academic Cancer Center. Cancer Control. 24(2). 120–124. 1 indexed citations

15.

Li, Hui, Yitan Zhu, Elizabeth S. Burnside, et al.. (2016). MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays. Radiology. 281(2). 382–391. 373 indexed citations breakdown →

16.

Li, Hui, Yitan Zhu, Elizabeth S. Burnside, et al.. (2016). Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set. npj Breast Cancer. 2(1). 287 indexed citations breakdown →

17.

Burnside, Elizabeth S., Karen Drukker, Hui Li, et al.. (2015). Using computer‐extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage. Cancer. 122(5). 748–757. 54 indexed citations

18.

Net, Jose, et al.. (2014). Resident and Fellow Education Feature: US Evaluation of Axillary Lymph Nodes. Radiographics. 34(7). 1817–1818. 29 indexed citations

19.

Yepes, Monica, Fernando Collado‐Mesa, Jose Net, et al.. (2014). Can mammographic and sonographic imaging features predict the Oncotype DX™ recurrence score in T1 and T2, hormone receptor positive, HER2 negative and axillary lymph node negative breast cancers?. Breast Cancer Research and Treatment. 148(1). 117–123. 20 indexed citations

20.

Collado‐Mesa, Fernando, et al.. (2013). Contralateral Intramammary Silicone Lymphadenitis in a Patient with an Intact Standard Dual-Lumen Breast Implant in the Opposite Reconstructed Breast. Journal of Radiology Case Reports. 7(11). 24–31. 10 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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