William Baskett

629 total citations · 1 hit paper
23 papers, 359 citations indexed

About

William Baskett is a scholar working on Neurology, Infectious Diseases and Artificial Intelligence. According to data from OpenAlex, William Baskett has authored 23 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Neurology, 7 papers in Infectious Diseases and 6 papers in Artificial Intelligence. Recurrent topics in William Baskett's work include COVID-19 Clinical Research Studies (7 papers), Long-Term Effects of COVID-19 (7 papers) and COVID-19 and Mental Health (5 papers). William Baskett is often cited by papers focused on COVID-19 Clinical Research Studies (7 papers), Long-Term Effects of COVID-19 (7 papers) and COVID-19 and Mental Health (5 papers). William Baskett collaborates with scholars based in United States, Taiwan and Australia. William Baskett's co-authors include Chi‐Ren Shyu, Adnan I. Qureshi, Wei Huang, S. Hasan Naqvi, Iryna Lobanova, Camilo R. Gomez, Farhan Siddiq, Brandi R French, Daniel Shyu and Danny Myers and has published in prestigious journals such as Clinical Infectious Diseases, Stroke and Journal of Biomedical Informatics.

In The Last Decade

William Baskett

18 papers receiving 347 citations

Hit Papers

Acute Ischemic Stroke and COVID-19 2021 2026 2022 2024 2021 50 100 150

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
William Baskett United States 9 201 191 82 66 37 23 359
Danny Myers United States 5 161 0.8× 132 0.7× 62 0.8× 55 0.8× 34 0.9× 7 256
Murugesan Raju United States 5 134 0.7× 113 0.6× 50 0.6× 37 0.6× 39 1.1× 10 223
Meng Cao United States 4 205 1.0× 229 1.2× 41 0.5× 80 1.2× 38 1.0× 7 321
Brian C. Boursiquot United States 9 202 1.0× 146 0.8× 42 0.5× 118 1.8× 6 0.2× 13 500
Emmanuelle Sacco France 5 253 1.3× 377 2.0× 34 0.4× 38 0.6× 4 0.1× 11 533
Fan Leng China 3 277 1.4× 440 2.3× 48 0.6× 156 2.4× 7 0.2× 8 508
Jiatian Cao China 4 191 1.0× 423 2.2× 65 0.8× 108 1.6× 5 0.1× 10 518
Salah Eddine Oussama Kacimi Algeria 7 61 0.3× 108 0.6× 50 0.6× 20 0.3× 5 0.1× 18 280
Jorge Luna United States 7 81 0.4× 78 0.4× 98 1.2× 20 0.3× 15 0.4× 12 274
Joshua Lang United States 4 194 1.0× 313 1.6× 31 0.4× 74 1.1× 5 0.1× 5 441

Countries citing papers authored by William Baskett

Since Specialization
Citations

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

Fields of papers citing papers by William Baskett

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of William Baskett

This figure shows the co-authorship network connecting the top 25 collaborators of William Baskett. A scholar is included among the top collaborators of William Baskett 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 William Baskett. William Baskett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Shyu, Chi‐Ren, et al.. (2025). Effective Non-IID Degree Estimation for Robust Federated Learning in Healthcare Datasets. PubMed. 9(3). 437–464. 1 indexed citations
3.
Qureshi, Adnan I., William Baskett, Bruce Ovbiagele, et al.. (2025). Post 90-day outcomes of acute ischemic stroke patients following thrombectomy: analysis of real-world data. Frontiers in Neurology. 16. 1543101–1543101.
4.
Baskett, William, et al.. (2025). Identifying homogenous patient subgroups using transformer based hierarchical clustering of heterogeneous Mixed-Modality medical data. Journal of Biomedical Informatics. 169. 104878–104878.
5.
Qureshi, Adnan I., William Baskett, Niraj Arora, et al.. (2024). Assessment of Blood Pressure and Heart Rate Related Variables in Acute Stroke Patients Receiving Intravenous Antihypertensive Medication Infusions. Neurocritical Care. 41(2). 434–444. 1 indexed citations
6.
Qureshi, Adnan I., William Baskett, Wei Huang, S. Hasan Naqvi, & Chi‐Ren Shyu. (2022). New-Onset Dementia Among Survivors of Pneumonia Associated With Severe Acute Respiratory Syndrome Coronavirus 2 Infection. Open Forum Infectious Diseases. 9(4). ofac115–ofac115. 15 indexed citations
7.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2022). New cardiovascular events in the convalescent period among survivors of SARS-CoV-2 infection. International Journal of Stroke. 18(4). 437–444. 3 indexed citations
8.
Qureshi, Adnan I., William Baskett, Brandi R French, et al.. (2022). Outcomes with IV tenecteplase and IV alteplase for acute ischemic stroke with or without thrombectomy in real-world settings in the United States. Journal of Stroke and Cerebrovascular Diseases. 32(2). 106898–106898. 12 indexed citations
9.
Shae, Zon‐Yin, Yuan‐Yu Tsai, Che‐Yi Chou, et al.. (2022). Thoughts on Non-IID Data Impact in Healthcare with Federated Learning Medical Blockchain. 20–26. 2 indexed citations
10.
Yu, Li, et al.. (2022). RHPTree—Risk Hierarchical Pattern Tree for Scalable Long Pattern Mining. ACM Transactions on Knowledge Discovery from Data. 16(4). 1–33. 5 indexed citations
11.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Subarachnoid Hemorrhage and COVID-19: An Analysis of 282,718 Patients. World Neurosurgery. 151. e615–e620. 19 indexed citations
12.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Reinfection With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Patients Undergoing Serial Laboratory Testing. Clinical Infectious Diseases. 74(2). 294–300. 47 indexed citations
13.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Effect of Race and Ethnicity on In-Hospital Mortality in Patients with COVID-2019. Ethnicity & Disease. 31(3). 389–398. 14 indexed citations
14.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Intracerebral Hemorrhage and Coronavirus Disease 2019 in a Cohort of 282,718 Hospitalized Patients. Neurocritical Care. 36(1). 259–265. 10 indexed citations
15.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Utilization and Outcomes of Acute Revascularization Treatments in Ischemic Stroke Patients with SARS-CoV-2 Infection. Journal of Stroke and Cerebrovascular Diseases. 31(1). 106157–106157. 7 indexed citations
16.
Qureshi, Adnan I., William Baskett, Wei Huang, et al.. (2021). Acute Ischemic Stroke and COVID-19. Stroke. 52(3). 905–912. 188 indexed citations breakdown →
17.
Chela, Harleen, William Baskett, Karthik Gangu, et al.. (2021). Liver injury on admission linked to worse outcomes in COVID-19: an analysis of 14,138 patients. Translational Gastroenterology and Hepatology. 8. 4–4. 5 indexed citations
18.
Baskett, William, et al.. (2019). Exploratory Data Mining for Subgroup Cohort Discoveries and Prioritization. IEEE Journal of Biomedical and Health Informatics. 24(5). 1456–1468. 14 indexed citations
19.
Baskett, William, Matthew Spencer, & Chi‐Ren Shyu. (2017). Efficient GPU-accelerated extraction of imperfect inverted repeats from DNA sequences. 24 24. 516–520. 1 indexed citations
20.
Baskett, William, Matthew Spencer, & Chi‐Ren Shyu. (2016). Large scale extraction of perfect and imperfect DNA palindromes using in-memory computing. 850–857. 1 indexed citations

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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