Michal Rosen‐Zvi

4.6k total citations · 2 hit papers
56 papers, 2.8k citations indexed

About

Michal Rosen‐Zvi is a scholar working on Artificial Intelligence, Infectious Diseases and Virology. According to data from OpenAlex, Michal Rosen‐Zvi has authored 56 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 10 papers in Infectious Diseases and 9 papers in Virology. Recurrent topics in Michal Rosen‐Zvi's work include HIV Research and Treatment (9 papers), Neural Networks and Applications (9 papers) and HIV/AIDS drug development and treatment (8 papers). Michal Rosen‐Zvi is often cited by papers focused on HIV Research and Treatment (9 papers), Neural Networks and Applications (9 papers) and HIV/AIDS drug development and treatment (8 papers). Michal Rosen‐Zvi collaborates with scholars based in Israel, United States and Germany. Michal Rosen‐Zvi's co-authors include Padhraic Smyth, Mark Steyvers, Thomas Griffiths, Thomas L. Griffiths, Max Welling, Geoffrey E. Hinton, Yair Weiss, Amit Gruber, Chaitanya Chemudugunta and Maurizio Zazzi and has published in prestigious journals such as The Lancet, Physical Review Letters and Nature Communications.

In The Last Decade

Michal Rosen‐Zvi

52 papers receiving 2.7k citations

Hit Papers

align trajectories sort by overperformance

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.

The author-topic model for authors and documents

2004 877 citations Michal Rosen‐Zvi, Thomas Griffiths et al. Uncertainty in Artificial Intelligence profile →
Exponential Family Harmoniums with an Application to Information Retrieval

2004 264 citations Max Welling, Michal Rosen‐Zvi et al. Neural Information Processing Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michal Rosen‐Zvi Israel	19	1.7k	626	433	375	281	56	2.8k
Yue Lu China	25	918 0.5×	451 0.7×	78 0.2×	645 1.7×	216 0.8×	124	2.5k
Ming Zhang China	31	1.7k 1.0×	1.1k 1.8×	408 0.9×	283 0.8×	220 0.8×	126	3.2k
Timothy Baldwin Australia	32	2.0k 1.2×	612 1.0×	263 0.6×	209 0.6×	1.3k 4.6×	126	4.3k
Taketoshi Yoshida Japan	23	856 0.5×	553 0.9×	61 0.1×	123 0.3×	343 1.2×	92	2.6k
Christopher Meek United States	15	1.6k 1.0×	578 0.9×	90 0.2×	347 0.9×	233 0.8×	41	2.5k
Cornelia Caragea United States	29	2.0k 1.2×	551 0.9×	214 0.5×	228 0.6×	418 1.5×	151	3.1k
Ying Shen China	32	1.6k 1.0×	329 0.5×	83 0.2×	424 1.1×	814 2.9×	171	3.4k
Ruifeng Xu China	35	2.6k 1.5×	357 0.6×	77 0.2×	343 0.9×	1.2k 4.4×	216	4.7k
Qian Liu China	23	899 0.5×	184 0.3×	82 0.2×	258 0.7×	295 1.0×	129	1.9k

Countries citing papers authored by Michal Rosen‐Zvi

Since Specialization

Citations

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

Fields of papers citing papers by Michal Rosen‐Zvi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michal Rosen‐Zvi. 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 Michal Rosen‐Zvi. The network helps show where Michal Rosen‐Zvi may publish in the future.

Co-authorship network of co-authors of Michal Rosen‐Zvi

This figure shows the co-authorship network connecting the top 25 collaborators of Michal Rosen‐Zvi. A scholar is included among the top collaborators of Michal Rosen‐Zvi 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 Michal Rosen‐Zvi. Michal Rosen‐Zvi 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

Heller, Nicholas, Betty Wang, Rebecca A. Campbell, et al.. (2025). AUTOMATING RENAL CANCER CHART REVIEW USING LARGE LANGUAGE MODELS. Urologic Oncology Seminars and Original Investigations. 43(3). 57–58. 1 indexed citations

Zeng, Li, Kenli Li, Zhimin Fu, et al.. (2024). A molecular video-derived foundation model for scientific drug discovery. Nature Communications. 15(1). 9696–9696. 17 indexed citations

Rabinovici‐Cohen, Simona, et al.. (2024). From Pixels to Diagnosis: Algorithmic Analysis of Clinical Oral Photos for Early Detection of Oral Squamous Cell Carcinoma. Cancers. 16(5). 1019–1019. 10 indexed citations

Qiu, Yunguang, et al.. (2024). A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain. Cell Reports Methods. 4(10). 100865–100865. 4 indexed citations

Ghisoni, Francesco, Giovanni Visonà, Roman Kern, et al.. (2023). Explainable AI in Biomedical Research: A Systematic Review and Meta-Analysis. SSRN Electronic Journal. 1 indexed citations

Ozery-Flato, Michal, et al.. (2023). Impact of the COVID-19 Pandemic on Clinical Findings in Medical Imaging Exams in a Nationwide Israeli Health Organization: Observational Study. JMIR Formative Research. 7. e42930–e42930. 1 indexed citations

Tlusty, Tsvi, et al.. (2022). Virtual Biopsy by Using Artificial Intelligence–based Multimodal Modeling of Binational Mammography Data. Radiology. 306(3). e220027–e220027. 10 indexed citations

Ozery-Flato, Michal, et al.. (2022). Predictive and Causal Analysis of No-Shows for Medical Exams During COVID-19: A Case Study of Breast Imaging in a Nationwide Israeli Health Organization. PubMed Central. 1 indexed citations

Rabinovici‐Cohen, Simona, et al.. (2022). Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy. Cancers. 14(16). 3848–3848. 20 indexed citations

10.

Born, Jannis, David Beymer, Deepta Rajan, et al.. (2021). On the role of artificial intelligence in medical imaging of COVID-19. Patterns. 2(6). 100269–100269. 38 indexed citations

11.

Kashyap, Aditya, Maria Anna Rapsomaniki, Anna Fomitcheva Khartchenko, et al.. (2021). Quantification of tumor heterogeneity: from data acquisition to metric generation. Trends in biotechnology. 40(6). 647–676. 46 indexed citations

12.

Born, Jannis, David Beymer, Deepta Rajan, et al.. (2021). On the role of artificial intelligence in medical imaging of COVID-19. Patterns. 2(8). 100330–100330. 11 indexed citations

13.

Akselrod-Ballin, Ayelet, Michal Chorev, Yoel Shoshan, et al.. (2019). Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms. Radiology. 292(2). 331–342. 126 indexed citations

14.

Falconer, Erin, Tal El‐Hay, John P. Docherty, et al.. (2017). Integrated multisystem analysis in a mental health and criminal justice ecosystem. PubMed. 2014. 526–33. 3 indexed citations

15.

Zazzi, Maurizio, Francesca Incardona, Michal Rosen‐Zvi, et al.. (2012). Predicting Response to Antiretroviral Treatment by Machine Learning: The EuResist Project. Intervirology. 55(2). 123–127. 44 indexed citations

16.

Prosperi, Mattia, Michal Rosen‐Zvi, André Altmann, et al.. (2011). Correction: Antiretroviral Therapy Optimisation without Genotype Resistance Testing: A Perspective on Treatment History Based Models. PLoS ONE. 6(4). 1 indexed citations

17.

Gruber, Amit, Yair Weiss, & Michal Rosen‐Zvi. (2007). Hidden Topic Markov Models. International Conference on Artificial Intelligence and Statistics. 163–170. 166 indexed citations

18.

Welling, Max, Michal Rosen‐Zvi, & Geoffrey E. Hinton. (2004). Exponential Family Harmoniums with an Application to Information Retrieval. Neural Information Processing Systems. 17. 1481–1488. 264 indexed citations breakdown →

19.

Rosen‐Zvi, Michal, Thomas Griffiths, Mark Steyvers, & Padhraic Smyth. (2004). The author-topic model for authors and documents. Uncertainty in Artificial Intelligence. 487–494. 877 indexed citations breakdown →

20.

Steyvers, Mark, Padhraic Smyth, Michal Rosen‐Zvi, & Thomas L. Griffiths. (2004). Probabilistic author-topic models for information discovery. 306–315. 401 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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