Danielle L. Mowery
- Artificial Intelligence top 5%
- Molecular Biology
- Social Psychology top 10%
- General Health Professions top 10%
- Epidemiology
- Co-authors
- Wendy W. ChapmanMike ConwayBrett R. SouthSumithra VelupillaiCraig J. BryanMaria KvistBrian E. ChapmanSalomeh Keyhani
- Topics
- Biomedical Text Mining and Ontologies (29 papers)Topic Modeling (19 papers)Natural Language Processing Techniques (15 papers)
- Partner nations
- United StatesSwedenAustralia
In The Last Decade
Danielle L. Mowery
69 papers receiving 906 citations
Peers
Comparison fields: 5 of 114
- Artificial Intelligence 399
- Molecular Biology 260
- Social Psychology 127
- General Health Professions 120
- Epidemiology 115
Countries citing papers authored by Danielle L. Mowery
This map shows the geographic impact of Danielle L. Mowery'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 Danielle L. Mowery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle L. Mowery more than expected).
Fields of papers citing papers by Danielle L. Mowery
This network shows the impact of papers produced by Danielle L. Mowery. 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 Danielle L. Mowery. The network helps show where Danielle L. Mowery may publish in the future.
Co-authorship network of co-authors of Danielle L. Mowery
This figure shows the co-authorship network connecting the top 25 collaborators of Danielle L. Mowery. A scholar is included among the top collaborators of Danielle L. Mowery 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 Danielle L. Mowery. Danielle L. Mowery is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 4 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 2 | |
| 11 | 7 | |
| 12 | 7 | |
| 13 | 10 | |
| 14 | 7 | |
| 15 | RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. | 3 |
| 16 | Towards Automatically Classifying Depressive Symptoms from Twitter Data for Population Health | 26 |
| 17 | 55 | |
| 18 | Developing a Knowledge Base for Detecting Carotid Stenosis with pyConText. | 2 |
| 19 | Medical diagnosis lost in translation -- Analysis of uncertainty and negation expressions in English and Swedish clinical texts | 9 |
| 20 | On the Road Towards Developing a Publicly Available Corpus of De-identified Clinical Texts. | 1 |
About Danielle L. Mowery
Danielle L. Mowery is a scholar working on Health Informatics, Applied Psychology and Family Practice, having authored 73 papers that have together received 936 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (29 papers), Topic Modeling (19 papers) and Natural Language Processing Techniques (15 papers). The work is most often cited by research in Health Informatics (68 citations), Health Information Management (101 citations) and Artificial Intelligence (399 citations). Danielle L. Mowery has collaborated with scholars based in United States, Sweden and Australia. Frequent co-authors include Wendy W. Chapman, Mike Conway, Brett R. South, Sumithra Velupillai, Craig J. Bryan, Maria Kvist, Brian E. Chapman, Salomeh Keyhani, Hilary A. Smith and Hercules Dalianis. Their work appears in journals such as PLoS ONE, Journal of the American Geriatrics Society and American Journal of Preventive Medicine.
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.