Don Perugini

740 total citations · 1 hit paper
23 papers, 425 citations indexed

About

Don Perugini is a scholar working on Public Health, Environmental and Occupational Health, Pediatrics, Perinatology and Child Health and Artificial Intelligence. According to data from OpenAlex, Don Perugini has authored 23 papers receiving a total of 425 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Public Health, Environmental and Occupational Health, 8 papers in Pediatrics, Perinatology and Child Health and 8 papers in Artificial Intelligence. Recurrent topics in Don Perugini's work include Reproductive Biology and Fertility (9 papers), Assisted Reproductive Technology and Twin Pregnancy (7 papers) and Multi-Agent Systems and Negotiation (6 papers). Don Perugini is often cited by papers focused on Reproductive Biology and Fertility (9 papers), Assisted Reproductive Technology and Twin Pregnancy (7 papers) and Multi-Agent Systems and Negotiation (6 papers). Don Perugini collaborates with scholars based in Australia, United States and Türkiye. Don Perugini's co-authors include Michelle Perugini, Sonya M. Diakiw, Matthew VerMilyea, Jonathan M. M. Hall, Adrian Johnston, Andrew Miller, A. Picou, M. Abou Dakka, Dale Lambert and Adrian R. Pearce and has published in prestigious journals such as Scientific Reports, Human Reproduction and Fertility and Sterility.

In The Last Decade

Don Perugini

23 papers receiving 390 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.

Development of an artificial intelligence-based assessment model for prediction of embryo viability using static images captured by optical light microscopy during IVF

2020 186 citations Matthew VerMilyea, Jonathan M. M. Hall et al. Human Reproduction profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Don Perugini Australia	9	205	153	108	106	53	23	425
Seyed Abolghasem Mirroshandel Iran	12	174 0.8×	46 0.3×	182 1.7×	200 1.9×	26 0.5×	41	568
Shujin Zhu China	12	71 0.3×	6 0.0×	58 0.5×	129 1.2×	14 0.3×	41	467
Yuan‐Yu Tsai Taiwan	12	20 0.1×	46 0.3×	6 0.1×	97 0.9×	23 0.4×	40	486
Chris Fawcett Canada	10	42 0.2×	120 0.8×	9 0.1×	118 1.1×	1 0.0×	17	378
Ian Huang United States	5	42 0.2×	21 0.1×	19 0.2×	74 0.7×	4 0.1×	7	285
Luca Bonomi United States	10	93 0.5×	3 0.0×	4 0.0×	300 2.8×	28 0.5×	29	490
Jiahao Wu China	11	21 0.1×	24 0.2×	30 0.3×	11 0.1×	2 0.0×	51	378
Yunshan Chen China	11	58 0.3×	83 0.5×	6 0.1×	14 0.1×		39	347
Deepika Gopukumar United States	4	22 0.1×	5 0.0×	2 0.0×	97 0.9×	30 0.6×	6	318
K. Kannan India	10	16 0.1×	12 0.1×	13 0.1×	39 0.4×		35	294

Countries citing papers authored by Don Perugini

Since Specialization

Citations

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

Fields of papers citing papers by Don Perugini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Don Perugini

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

Hall, Jonathan M. M., Trung Van Nguyen, Don Perugini, et al.. (2024). Use of federated learning to develop an artificial intelligence model predicting usable blastocyst formation from pre-ICSI oocyte images. Reproductive BioMedicine Online. 49(6). 104403–104403. 2 indexed citations

VerMilyea, Matthew, Sonya M. Diakiw, Carla Giménez, et al.. (2023). DEVELOPMENT OF A NON-INVASIVE ARTIFICIAL INTELLIGENCE ALGORITHM FOR IDENTIFICATION OF EUPLOID EMBRYOS WITH HIGH MORPHOLOGICAL QUALITY DURING IVF. Fertility and Sterility. 120(4). e76–e77. 1 indexed citations

Diakiw, Sonya M., et al.. (2023). Efficient automated error detection in medical data using deep-learning and label-clustering. Scientific Reports. 13(1). 19587–19587. 3 indexed citations

Diakiw, Sonya M., Jonathan M. M. Hall, Matthew VerMilyea, et al.. (2022). An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos. Reproductive BioMedicine Online. 45(6). 1105–1117. 39 indexed citations

Dakka, M. Abou, Sonya M. Diakiw, Matthew VerMilyea, et al.. (2022). A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data. Scientific Reports. 12(1). 8888–8888. 40 indexed citations

Diakiw, Sonya M., et al.. (2022). A NON-INVASIVE ARTIFICIAL INTELLIGENCE (AI) ALGORITHM CAN PREDICT COMPETENCE OF DENUDED OOCYTES FROM IMAGES TAKEN PRIOR TO INTRACYTOPLASMIC SPERM INJECTION (ICSI). Fertility and Sterility. 118(4). e113–e113. 1 indexed citations

Diakiw, Sonya M., Jonathan M. M. Hall, Matthew VerMilyea, et al.. (2022). Development of an artificial intelligence model for predicting the likelihood of human embryo euploidy based on blastocyst images from multiple imaging systems during IVF. Human Reproduction. 37(8). 1746–1759. 59 indexed citations

Diakiw, Sonya M., Matthew VerMilyea, Jonathan M. M. Hall, et al.. (2021). O-222 An artificial intelligence model that was trained on pregnancy outcomes for embryo viability assessment is highly correlated with Gardner Score. Human Reproduction. 36(Supplement_1). 1 indexed citations

Dakka, M. Abou, Jonathan M. M. Hall, Sonya M. Diakiw, et al.. (2021). Automated detection of poor-quality data: case studies in healthcare. Scientific Reports. 11(1). 18005–18005. 16 indexed citations

10.

Dakka, M. Abou, Matthew VerMilyea, Don Perugini, et al.. (2020). IDENTIFYING INHERENT POOR QUALITY EMBRYO DATA USING ARTIFICIAL INTELLIGENCE TO IMPROVE AI PERFORMANCE AND CLINICAL REPORTING. Fertility and Sterility. 114(3). e148–e148. 1 indexed citations

11.

VerMilyea, Matthew, Jonathan M. M. Hall, Don Perugini, et al.. (2019). Artificial intelligence: non-invasive detection of morphological features associated with abnormalities in chromosomes 21 and 16. Fertility and Sterility. 112(3). e237–e238. 2 indexed citations

12.

Perugini, Don & Michelle Perugini. (2014). Characterised and personalised predictive-prescriptive analytics using agent-based simulation. International Journal of Data Analysis Techniques and Strategies. 6(3). 209–209. 3 indexed citations

13.

Perugini, Don, et al.. (2007). Distributed Deliberative Planning with Partial Observability: Heuristic Approaches. 11. 407–412. 1 indexed citations

14.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2006). From Single Static to Multiple Dynamic Combinatorial Auctions. IEEE/WIC/ACM International Conference on Intelligent Agent Technology. 443–446. 9 indexed citations

15.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2004). Agent-Based Global Transportation Scheduling in Military Logistics. Swinburne Research Bank (Swinburne University of Technology). 3. 1278–1279. 5 indexed citations

16.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2004). A distributed agent approach to global transportation scheduling. Figshare. 18–24. 12 indexed citations

17.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2003). A Distributed Agent Approachto Global Transportation Scheduling. IEEE/WIC/ACM International Conference on Intelligent Agent Technology. 18–24. 2 indexed citations

18.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2003). Distributed information fusion agents. 86–93. 15 indexed citations

19.

Perugini, Don, et al.. (2003). Dynamic agent systems in the CoAX Binni 2002 experiment. 205–212. 9 indexed citations

20.

Perugini, Don, Dale Lambert, Leon Sterling, & Adrian R. Pearce. (2002). Agents for military logistic planning. Swinburne Research Bank (Swinburne University of Technology). 35. 7 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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