Mark Sak

404 citations
27 papers · 318 indexed · h-index 9
Topics
AI in cancer detection (18 papers)Digital Radiography and Breast Imaging (17 papers)Ultrasound Imaging and Elastography (10 papers)
Partner nations
United StatesCanadaChina

In The Last Decade

Mark Sak

26 papers receiving 304 citations

Peers

Mark Sak
Comparison fields: 5 of 46
  • Radiology, Nuclear Medicine and Imaging 176
  • Artificial Intelligence 133
  • Pulmonary and Respiratory Medicine 123
  • Biomedical Engineering 120
  • Oncology 57
Replace Lisa Bey‐Knight with:
Lisa Bey‐Knight United States
C Glide United States
Mirjam Facius Germany
Olsi Rama United States
Wei-Chih Shen Taiwan
Earle Holsapple United States
K.M. Hiltawsky Germany
Frederick Au Canada
Afsaneh Alikhassi Iran
A Jung Chu South Korea
Mark Sak relative to Lisa Bey‐Knight United States Lisa Bey‐Knight's profile →
Citations per field
00.5×5.5×
Lisa Bey‐Knight · 1×
Citations per year

Countries citing papers authored by Mark Sak

Since Specialization
Citations

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

Fields of papers citing papers by Mark Sak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Sak

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Sak. A scholar is included among the top collaborators of Mark Sak 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 Mark Sak. Mark Sak 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
#WorkIndexed citations
1 2
2 5
3 13
4 27
5 5
6 0
7 1
8 1
9 5
10 53
11 22
12 31
13 2
14 6
15 14
16 52
17
The Role Of Tissue Sound Speed As A Surrogate Marker Of Breast Density
3
18 7
19 6
20 5

About Mark Sak

Mark Sak is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 27 papers that have together received 318 indexed citations. Recurring topics across this work include AI in cancer detection (18 papers), Digital Radiography and Breast Imaging (17 papers) and Ultrasound Imaging and Elastography (10 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (176 citations), Artificial Intelligence (133 citations) and Pulmonary and Respiratory Medicine (123 citations). Mark Sak has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Peter J. Littrup, Neb Duric, Gretchen L. Gierach, Mark E. Sherman, Lisa Bey‐Knight, Cuiping Li, Haythem Ali, Nebojsa Duric, Norman F. Boyd and Rachel F. Brem. Their work appears in journals such as Sensors, Medical Physics and BioMed Research International.

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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