Mikhail Milchenko

2.4k citations
23 papers · 1.2k · 1 hit paper · h-index 10

Impact in

Papers in

Mikhail Milchenko

22 papers receiving 1.1k citations

Mikhail Milchenko's Hit Papers

Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data 2020 · 781 citations
7810+2+4Years since publication250500750

Peers

Mikhail Milchenko
Comparison fields: 5 of 99
  • Health Informatics 142
  • Radiology, Nuclear Medicine and Imaging 357
  • Artificial Intelligence 458
  • Cognitive Neuroscience 178
  • Neurology 73
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Citations per field
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Citations per year

Countries citing papers authored by Mikhail Milchenko

Since Specialization
Citations

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

Fields of papers citing papers by Mikhail Milchenko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mikhail Milchenko, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mikhail Milchenko Line = papers co-authored together Mikhail Milchenko links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
Hit paper breakdown →
2020781
2 201297
3 201749
4 201845
5 202141
6 202039
7 202028
8 201812
9 202111
10 201310
11 20147
12 20066
13 20136
14 20186
15 20155
16 20204
17 20233
18 20163
19 20203
20 20191

About Mikhail Milchenko

Mikhail Milchenko is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Genetics, Neurology and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced Neuroimaging Techniques and Applications (5 papers), Functional Brain Connectivity Studies (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Advanced MRI Techniques and Applications (4 papers), Neurological disorders and treatments (3 papers), MRI in cancer diagnosis (3 papers), Glioma Diagnosis and Treatment (3 papers) and Medical Image Segmentation Techniques (2 papers). The work is most often cited by research in Health Informatics (142 citations), Radiology, Nuclear Medicine and Imaging (357 citations), Artificial Intelligence (458 citations), Cognitive Neuroscience (178 citations) and Neurology (73 citations). Mikhail Milchenko has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include Brandon Edwards, Jason Martin, Micah Sheller, Aikaterini Kotrotsou, G. Anthony Reina, Daniel C. Marcus, Spyridon Bakas, Sarthak Pati, Weilin Xu and Rivka R. Colen. Their work appears in journals such as PLoS ONE, Neuroinformatics, Radiology Artificial Intelligence, Movement Disorders and Blood.

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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