Michael Albert

849 citations
22 papers · 638 · h-index 12

Impact in

Papers in

Michael Albert

21 papers receiving 614 citations

Peers

Michael Albert
Comparison fields: 5 of 63
  • Radiology, Nuclear Medicine and Imaging 465
  • Pulmonary and Respiratory Medicine 468
  • Artificial Intelligence 206
  • Biomedical Engineering 257
  • Radiation 33
Replace Alan H. Baydush with:
Alan H. Baydush United States
Oscar A. Debats Netherlands
Diksha Sharma United States
Philip Caligiuri United States
Matin Hosseinzadeh United States
Nico Lanconelli Italy
Xinran Zhong United States
Ted W. Way United States
Heber MacMahon United States
Margarita Chevalier Spain
Michael Albert relative to Alan H. Baydush United States Alan H. Baydush's profile →
Citations per field
00.5×2.9×
Alan H. Baydush · 1×
Citations per year

Countries citing papers authored by Michael Albert

Since Specialization
Citations

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

Fields of papers citing papers by Michael Albert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Michael Albert, 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 Michael Albert Line = papers co-authored together Michael Albert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002115
2 200772
3 200268
4 200566
5 199662
6 200351
7 200347
8 200040
9 200534
10 200624
11 200316
12 200315
13 20028
14 19965
15 20055
16 19984
17 20022
18 19901
19 20031
20 20021

About Michael Albert

Michael Albert is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Computer Vision and Pattern Recognition and Biomedical Engineering, having authored 22 papers that have together received 638 indexed citations. Recurring topics across this work include Digital Radiography and Breast Imaging (12 papers), Medical Imaging Techniques and Applications (9 papers), AI in cancer detection (6 papers), Advanced X-ray and CT Imaging (3 papers), Advanced Image Fusion Techniques (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Image and Signal Denoising Methods (2 papers) and Breast Lesions and Carcinomas (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (465 citations), Pulmonary and Respiratory Medicine (468 citations), Artificial Intelligence (206 citations), Biomedical Engineering (257 citations) and Radiation (33 citations). Michael Albert has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Andrew D. A. Maidment, Predrag R. Bakić, D. Brzaković, Ann-Katherine Carton, Emily F. Conant, Mitchell D. Schnall, Abba Μ. Krieger, Ethan J. Halpern, Charles E. Metz and Hilde Bosmans. Their work appears in journals such as Medical Physics, Academic Radiology, Journal of Surgical Oncology, IFAC-PapersOnLine and Lund University Publications (Lund University).

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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