Nhan Do

73 papers receiving 1.2k citations

Nhan Do's Hit Papers

AI in Medical Imaging Informatics: Current Challenges and Future Directions 2020 · 361 citations
3610+2+4Years since publication100200300

Peers

Nhan Do
Comparison fields: 5 of 140
  • Health Informatics 88
  • Health Information Management 100
  • Geriatrics and Gerontology 74
  • Medical Terminology 4
  • Infectious Diseases 180
Replace Zahra Raisi‐Estabragh with:
Zahra Raisi‐Estabragh United Kingdom
Tahmina Nasrin Poly Taiwan
Evangelia Christodoulou Germany
Robert Freeman United States
Nathalie Conrad United Kingdom
Joseph E. Ebinger United States
Milena Gianfrancesco United States
Julián Acosta United States
Stephen A. Deppen United States
Shelly Soffer Israel
Nhan Do relative to Zahra Raisi‐Estabragh United Kingdom Zahra Raisi‐Estabragh's profile →
Citations per field
00.5×3.7×
Zahra Raisi‐Estabragh · 1×
Citations per year

Countries citing papers authored by Nhan Do

Since Specialization
Citations

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

Fields of papers citing papers by Nhan Do

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1
AI in Medical Imaging Informatics: Current Challenges and Future Directions
Hit paper breakdown →
2020361
2 200180
3 202169
4 202068
5 202155
6 202139
7 201138
8 200736
9 202129
10 200728
11 202228
12 202027
13 200424
14 202223
15
Implementation of RxNorm as a terminology mediation standard for exchanging pharmacy medication between federal agencies.
200623
16 202120
17 202018
18 202118
19 201515
20 202214

About Nhan Do

Nhan Do is a scholar working on Oncology, Artificial Intelligence, Infectious Diseases, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 85 papers that have together received 1.2k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (11 papers), SARS-CoV-2 and COVID-19 Research (9 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Multiple Myeloma Research and Treatments (7 papers), AI in cancer detection (7 papers), Frailty in Older Adults (7 papers), Biomedical Text Mining and Ontologies (6 papers) and COVID-19 and healthcare impacts (6 papers). The work is most often cited by research in Health Informatics (88 citations), Health Information Management (100 citations), Geriatrics and Gerontology (74 citations), Medical Terminology (4 citations) and Infectious Diseases (180 citations). Nhan Do has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Nathanael R. Fillmore, Mary T. Brophy, Jennifer La, Amir A. Amini, Andreas S. Panayides, Alistair A. Young, David J. Foran, Konstantina S. Nikita, Sotirios A. Tsaftaris and Spyretta Golemati. Their work appears in journals such as Blood, Journal of Clinical Oncology, Blood Advances, JAMA Network Open and JCO Clinical Cancer Informatics.

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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