Patrick Wu

13 papers receiving 610 citations

Patrick Wu's Hit Papers

Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation 2019 · 264 citations
2640+2+4Years since publication50100150200250

Peers

Patrick Wu
Comparison fields: 5 of 97
  • Health Informatics 25
  • Computational Mathematics 8
  • Health Information Management 53
  • Genetics 112
  • Cardiology and Cardiovascular Medicine 62
Replace Peter Speltz with:
Peter Speltz United States
Puneet Batra United States
Yong Mong Bee Singapore
Carla Márquez‐Luna United States
Joseph B. Leader United States
Lisa A. Bastarache United States
Dan Masys United States
Jacqueline Corrigan‐Curay United States
V. Eric Kerchberger United States
Salim Janmohamed United Kingdom
Patrick Wu relative to Peter Speltz United States Peter Speltz's profile →
Citations per field
00.5×4.5×
Peter Speltz · 1×
Citations per year

Countries citing papers authored by Patrick Wu

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1
Mapping ICD-10 and ICD-10-CM Codes to Phecodes: Workflow Development and Initial Evaluation
Hit paper breakdown →
2019264
2 2019132
3 202237
4 202336
5 201934
6 201928
7 202125
8 202416
9 202111
10 202111
11 20249
12 19917
13 20255
14 20250
15 20220

About Patrick Wu

Patrick Wu is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Immunology, Cardiology and Cardiovascular Medicine and Artificial Intelligence, having authored 15 papers that have together received 615 indexed citations. Recurring topics across this work include Biosimilars and Bioanalytical Methods (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Protein purification and stability (2 papers), Bioinformatics and Genomic Networks (2 papers), Machine Learning in Healthcare (2 papers), Statistical Methods in Clinical Trials (2 papers), Cardiovascular Health and Risk Factors (2 papers) and Pharmacogenetics and Drug Metabolism (1 paper). The work is most often cited by research in Health Informatics (25 citations), Computational Mathematics (8 citations), Health Information Management (53 citations), Genetics (112 citations) and Cardiology and Cardiovascular Medicine (62 citations). Patrick Wu has collaborated with scholars based in United States, Switzerland and Australia. Frequent co-authors include Juan Zhao, Wei‐Qi Wei, Joshua C. Denny, QiPing Feng, Xiangrui Meng, Harry Campbell, Lisa Bastarache, Aliya Gifford, Evropi Τheodoratou and Robert J. Carroll. Their work appears in journals such as mAbs, Journal of Biomedical Informatics, Journal of the American Medical Informatics Association, Frontiers in Pharmacology and Circulation.

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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