Julia Mai

525 citations
27 papers · 346 · h-index 9

Impact in

Papers in

Julia Mai

24 papers receiving 345 citations

Peers

Julia Mai
Comparison fields: 5 of 43
  • Ophthalmology 242
  • Radiology, Nuclear Medicine and Imaging 281
  • Health Informatics 2
  • Pulmonary and Respiratory Medicine 46
  • Biophysics 8
Replace Dmitrii Lachinov with:
Dmitrii Lachinov Austria
Neha Anegondi United States
Tina Herold Germany
Michael Dubow United States
Duriye Damla Sevgi United States
Mingzhen Yuan China
Ermete Giancipoli Italy
Masanori Niki Japan
Paola Marolo Italy
Hae Min Kang South Korea
Julia Mai relative to Dmitrii Lachinov Austria Dmitrii Lachinov's profile →
Citations per field
00.5×12×
Dmitrii Lachinov · 1×
Citations per year

Countries citing papers authored by Julia Mai

Since Specialization
Citations

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

Fields of papers citing papers by Julia Mai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Julia Mai, 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 Julia Mai Line = papers co-authored together Julia Mai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202271
2 201859
3 202250
4 202228
5 202322
6 202219
7 202318
8 202414
9 202410
10 20248
11 20247
12 20247
13 20246
14 20244
15 20244
16 20243
17 20243
18 20232
19
Identification of initial events leading to outer retinal atrophy in age-related macular degeneration using deep learning quantifications
20212
20 20242

About Julia Mai

Julia Mai is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology, Biomedical Engineering, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 27 papers that have together received 346 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (21 papers), Retinal Diseases and Treatments (18 papers), Glaucoma and retinal disorders (7 papers), Retinal and Optic Conditions (7 papers), Optical Coherence Tomography Applications (6 papers), Digital Imaging for Blood Diseases (2 papers), Acute Ischemic Stroke Management (2 papers) and Retinal and Macular Surgery (2 papers). The work is most often cited by research in Ophthalmology (242 citations), Radiology, Nuclear Medicine and Imaging (281 citations), Health Informatics (2 citations), Pulmonary and Respiratory Medicine (46 citations) and Biophysics (8 citations). Julia Mai has collaborated with scholars based in Austria, Switzerland and United Kingdom. Frequent co-authors include Hrvoje Bogunović, Ursula Schmidt‐Erfurth, Sophie Riedl, Gregor S. Reiter, Dmitrii Lachinov, Wolf‐Dieter Vogl, Christoph Grechenig, Alex McKeown, Marc‐Oliver Grimm and Ulf Teichgräber. Their work appears in journals such as Investigative Ophthalmology & Visual Science, Ophthalmology Retina, Scientific Reports, Translational Vision Science & Technology and IEEE Transactions on Medical Imaging.

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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