Casey Ta

43 papers receiving 688 citations

Peers

Casey Ta
Comparison fields: 5 of 105
  • Health Informatics 60
  • Health Information Management 40
  • Artificial Intelligence 158
  • Radiology, Nuclear Medicine and Imaging 90
  • Biomaterials 46
Replace Patrick D. Tyler with:
Patrick D. Tyler United States
Xun Xiao China
Lin Guo China
Aleidy Silva United States
Ryan Goosen Switzerland
S. P. Somashekhar India
Yuxin Shi China
Qingxia Wu China
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Casey Ta relative to Patrick D. Tyler United States Patrick D. Tyler's profile →
Citations per field
00.5×3.2×
Patrick D. Tyler · 1×
Citations per year

Countries citing papers authored by Casey Ta

Since Specialization
Citations

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

Fields of papers citing papers by Casey Ta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018111
2 201273
3 201950
4 201742
5 202037
6 201832
7 202421
8 202220
9 201919
10 202018
11 201917
12 201216
13 201915
14 201915
15 201415
16
Dependence of intraocular pressure on induced hypotension and posture during surgical anaesthesia.
198015
17 201914
18 201214
19 201914
20 196613

About Casey Ta

Casey Ta is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Molecular Biology and Genetics, having authored 48 papers that have together received 702 indexed citations. Recurring topics across this work include Ultrasound and Hyperthermia Applications (5 papers), Ultrasound Imaging and Elastography (4 papers), Photoacoustic and Ultrasonic Imaging (4 papers), Biomedical Text Mining and Ontologies (4 papers), Machine Learning in Healthcare (3 papers), Topic Modeling (3 papers), Ethics in Clinical Research (3 papers) and Data Quality and Management (2 papers). The work is most often cited by research in Health Informatics (60 citations), Health Information Management (40 citations), Artificial Intelligence (158 citations), Radiology, Nuclear Medicine and Imaging (90 citations) and Biomaterials (46 citations). Casey Ta has collaborated with scholars based in United States, South Korea and Russia. Frequent co-authors include Chunhua Weng, Andrew C. Kummel, Robert F. Mattrey, Ziran Li, Cong Liu, Yuko Kono, Tian Kang, Christopher V. Barback, Chi Yuan and Ning Shang. Their work appears in journals such as Journal of the American Medical Informatics Association, Journal of Biomedical Informatics, npj Digital Medicine, Journal of Vacuum Science & Technology B Nanotechnology and Microelectronics Materials Processing Measurement and Phenomena and Investigative Radiology.

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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