Michal Ozery-Flato

683 total citations
22 papers, 347 citations indexed

About

Michal Ozery-Flato is a scholar working on Artificial Intelligence, Genetics and Molecular Biology. According to data from OpenAlex, Michal Ozery-Flato has authored 22 papers receiving a total of 347 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Genetics and 4 papers in Molecular Biology. Recurrent topics in Michal Ozery-Flato's work include Machine Learning in Healthcare (5 papers), Artificial Intelligence in Healthcare (4 papers) and Genome Rearrangement Algorithms (4 papers). Michal Ozery-Flato is often cited by papers focused on Machine Learning in Healthcare (5 papers), Artificial Intelligence in Healthcare (4 papers) and Genome Rearrangement Algorithms (4 papers). Michal Ozery-Flato collaborates with scholars based in Israel, United States and Germany. Michal Ozery-Flato's co-authors include Ron Shamir, Michal Rosen‐Zvi, Liat Ein‐Dor, Yaara Goldschmidt, Chaim Linhart, Luba Trakhtenbrot, Shai Izraeli, Ranit Aharonov, Orrin Devinsky and Chris Clark and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Radiology.

In The Last Decade

Michal Ozery-Flato

21 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michal Ozery-Flato Israel 10 136 96 88 56 40 22 347
Masao Ueki Japan 13 189 1.4× 92 1.0× 73 0.8× 69 1.2× 8 0.2× 45 569
Christopher R. Bauer United States 9 193 1.4× 64 0.7× 72 0.8× 67 1.2× 8 0.2× 12 372
Yongjin Bao China 9 99 0.7× 51 0.5× 52 0.6× 10 0.2× 44 1.1× 15 360
Lorenz Adlung Germany 8 243 1.8× 58 0.6× 47 0.5× 11 0.2× 8 0.2× 15 455
Zachary B. Abrams United States 13 185 1.4× 41 0.4× 25 0.3× 26 0.5× 14 0.3× 36 487
Ivan Limongelli Italy 11 187 1.4× 20 0.2× 165 1.9× 15 0.3× 34 0.8× 19 370
Enrique J. deAndrés‐Galiana Spain 13 221 1.6× 41 0.4× 38 0.4× 3 0.1× 29 0.7× 30 534
Ying Sha China 10 102 0.8× 182 1.9× 11 0.1× 13 0.2× 6 0.1× 21 430
Tim Beck United Kingdom 15 528 3.9× 72 0.8× 282 3.2× 27 0.5× 8 0.2× 30 776
Brunilda Balliu United States 12 225 1.7× 27 0.3× 158 1.8× 11 0.2× 4 0.1× 27 479

Countries citing papers authored by Michal Ozery-Flato

Since Specialization
Citations

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

Fields of papers citing papers by Michal Ozery-Flato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michal Ozery-Flato. 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 Ozery-Flato. The network helps show where Michal Ozery-Flato may publish in the future.

Co-authorship network of co-authors of Michal Ozery-Flato

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

All Works

20 of 20 papers shown
1.
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
2.
Barkan, Ella, Kevin J. Cheng, Yoel Shoshan, et al.. (2025). Leveraging large language models to predict antibody biological activity against influenza A hemagglutinin. Computational and Structural Biotechnology Journal. 27. 1286–1295. 2 indexed citations
3.
Heller, Nicholas, Betty Wang, Rebecca A. Campbell, et al.. (2025). PD32-04 AUTOMATING RENAL CANCER CHART REVIEW USING LARGE LANGUAGE MODELS. The Journal of Urology. 213(5S).
4.
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
5.
Chorev, Michal, Adam Spiro, Ella Evron, et al.. (2023). Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment. PubMed. 2022. 385–394. 2 indexed citations
6.
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
7.
Cintas, Celia, et al.. (2022). A causal inference approach for estimating effects of non-pharmaceutical interventions during Covid-19 pandemic. PLoS ONE. 17(9). e0265289–e0265289. 8 indexed citations
8.
Shoshan, Yoel, Vadim Ratner, Ella Barkan, et al.. (2022). Artificial Intelligence for Reducing Workload in Breast Cancer Screening with Digital Breast Tomosynthesis. Radiology. 303(1). 69–77. 40 indexed citations
9.
Laifenfeld, Daphna, Chen Yanover, Michal Ozery-Flato, et al.. (2021). Emulated Clinical Trials from Longitudinal Real-World Data Efficiently Identify Candidates for Neurological Disease Modification: Examples from Parkinson’s Disease. Frontiers in Pharmacology. 12. 631584–631584. 12 indexed citations
10.
Ozery-Flato, Michal, et al.. (2020). Framework for identifying drug repurposing candidates from observational healthcare data. JAMIA Open. 3(4). 536–544. 16 indexed citations
11.
Ozery-Flato, Michal, Liat Ein‐Dor, Ranit Aharonov, et al.. (2016). Identifying and Investigating Unexpected Response to Treatment: A Diabetes Case Study. Big Data. 4(3). 148–159. 6 indexed citations
12.
Devinsky, Orrin, Michal Ozery-Flato, Ranit Aharonov, et al.. (2016). Changing the approach to treatment choice in epilepsy using big data. Epilepsy & Behavior. 56. 32–37. 52 indexed citations
13.
Ein‐Dor, Liat, et al.. (2014). Functional gene groups are concentrated within chromosomes, among chromosomes and in the nuclear space of the human genome. Nucleic Acids Research. 42(15). 9854–9861. 61 indexed citations
14.
Ozery-Flato, Michal, Tal El‐Hay, Ligita Ryliškytė, et al.. (2013). Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome. Diabetology & Metabolic Syndrome. 5(1). 36–36. 11 indexed citations
15.
Ozery-Flato, Michal & Ron Shamir. (2011). An O(n3/2log(n)) algorithm for sorting by reciprocal translocations. Journal of Discrete Algorithms. 9(4). 344–357. 2 indexed citations
16.
Ozery-Flato, Michal, Chaim Linhart, Luba Trakhtenbrot, Shai Izraeli, & Ron Shamir. (2011). Large-scale analysis of chromosomal aberrations in cancer karyotypes reveals two distinct paths to aneuploidy. Genome biology. 12(6). R61–R61. 39 indexed citations
17.
Ozery-Flato, Michal & Ron Shamir. (2009). Sorting Cancer Karyotypes by Elementary Operations. Journal of Computational Biology. 16(10). 1445–1460. 8 indexed citations
18.
Ozery-Flato, Michal & Ron Shamir. (2008). An O(n 3/2 √ log(n)) algorithm for sorting by reciprocal translocations. 1 indexed citations
19.
Ozery-Flato, Michal & Ron Shamir. (2007). Sorting by Reciprocal Translocations via Reversals Theory. Journal of Computational Biology. 14(4). 408–422. 4 indexed citations
20.
Ozery-Flato, Michal & Ron Shamir. (2003). TWO NOTES ON GENOME REARRANGEMENT. Journal of Bioinformatics and Computational Biology. 1(1). 71–94. 31 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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