Stella G. Machado
- Toxicology top 0.5%
- Computational Theory and Mathematics top 5%
- Statistics and Probability top 2%
- Pharmacology top 10%
- Oncology
- Co-authors
- Ana SzarfmanJoanne ZhangCharles E. LandSuminori AkibaNorihiko HayakawaMalcolm C. PikeMasayoshi TokunagaMeiyu Shen
- Topics
- Statistical Methods in Clinical Trials (5 papers)Advancements in Transdermal Drug Delivery (3 papers)Computational Drug Discovery Methods (3 papers)
- Partner nations
- United StatesIrelandThailand
In The Last Decade
Stella G. Machado
17 papers receiving 923 citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Toxicology 340
- Computational Theory and Mathematics 182
- Statistics and Probability 149
- Pharmacology 147
- Oncology 136
Countries citing papers authored by Stella G. Machado
This map shows the geographic impact of Stella G. Machado'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 Stella G. Machado with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stella G. Machado more than expected).
Fields of papers citing papers by Stella G. Machado
This network shows the impact of papers produced by Stella G. Machado. 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 Stella G. Machado. The network helps show where Stella G. Machado may publish in the future.
Co-authorship network of co-authors of Stella G. Machado
This figure shows the co-authorship network connecting the top 25 collaborators of Stella G. Machado. A scholar is included among the top collaborators of Stella G. Machado 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 Stella G. Machado. Stella G. Machado is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 7 | |
| 3 | 6 | |
| 4 | 5 | |
| 5 | 12 | |
| 6 | 79 | |
| 7 | 41 | |
| 8 | 1 | |
| 9 | Use of Screening Algorithms and Computer Systems to Efficiently Signal Higher-Than-Expected Combinations of Drugs and Events in the US FDA??s Spontaneous Reports Databasebreakdown → | 510 |
| 10 | 18 | |
| 11 | 97 | |
| 12 | 59 | |
| 13 | 40 | |
| 14 | 52 | |
| 15 | Assessment of interaction among three carcinogens on rat mammary carcinogenesis in a factorially designed experiment. | 5 |
| 16 | 4 | |
| 17 | 24 |
About Stella G. Machado
Stella G. Machado is a scholar working on Pharmaceutical Science, Statistics and Probability and Toxicology, having authored 17 papers that have together received 969 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (5 papers), Advancements in Transdermal Drug Delivery (3 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Toxicology (340 citations), Statistics and Probability (149 citations) and Computational Theory and Mathematics (182 citations). Stella G. Machado has collaborated with scholars based in United States, Ireland and Thailand. Frequent co-authors include Ana Szarfman, Joanne Zhang, Charles E. Land, Suminori Akiba, Norihiko Hayakawa, Malcolm C. Pike, Masayoshi Tokunaga, Meiyu Shen, Roger Williams and Lawrence J. Lesko. Their work appears in journals such as Science, Nature Reviews Drug Discovery and Biometrics.
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.