Michael Wayne Goodman

873 citations
34 papers · 638 indexed · h-index 15

Michael Wayne Goodman

32 papers receiving 590 citations

Peers

Michael Wayne Goodman
Comparison fields: 5 of 96
  • Pharmaceutical Science 260
  • Dermatology 148
  • Hepatology 57
  • Pharmacology 39
  • Clinical Biochemistry 26
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Citations per year

Countries citing papers authored by Michael Wayne Goodman

Since Specialization
Citations

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

Fields of papers citing papers by Michael Wayne Goodman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20210
2 20212
3
A Python Library for Deep Linguistic Resources
20192
4
PDF-to-Text Reanalysis for Linguistic Data Mining
20181
5
Resources for building applications with Dependency Minimal Recursion Semantics
201610
6 20164
7
Enriching ODIN
20142
8 20144
9 201412
10
Towards Creating Precision Grammars from Interlinear Glossed Text: Inferring Large-Scale Typological Properties
201316
11 201317
12 20122
13
Grammar Prototyping and Testing with the LinGO Grammar Matrix Customization System
201017
14 200917
15 199719
16 1988119
17 198714
18 19853
19 198421
20 198223

About Michael Wayne Goodman

Michael Wayne Goodman is a scholar working on Artificial Intelligence, Filtration and Separation, Dermatology, Pharmaceutical Science and Clinical Biochemistry, having authored 34 papers that have together received 638 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (17 papers), Speech and dialogue systems (6 papers), Semantic Web and Ontologies (5 papers), Biomedical Text Mining and Ontologies (3 papers), Amino Acid Enzymes and Metabolism (2 papers), Neonatal and fetal brain pathology (2 papers) and Advancements in Transdermal Drug Delivery (2 papers). The work is most often cited by research in Pharmaceutical Science (260 citations), Dermatology (148 citations), Hepatology (57 citations), Pharmacology (39 citations) and Clinical Biochemistry (26 citations). Michael Wayne Goodman has collaborated with scholars based in United States, United Kingdom and Singapore. Frequent co-authors include Brian Barry, Melvin P. Bubrick, Robert A. Gill, Emily M. Bender, Gerald R. Onstad, Philip L. Gould, William F. Keane, Leslie Zieve, Frank B. Cerra and Fei Xia. Their work appears in journals such as Language Resources and Evaluation, American Journal of Physiology-Gastrointestinal and Liver Physiology, Journal of Pharmacy and Pharmacology, International Journal of Pharmaceutics and The Journal of Pediatrics.

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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