Andrew D. Monk

590 total citations
11 papers, 393 citations indexed

About

Andrew D. Monk is a scholar working on Neurology, Epidemiology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Andrew D. Monk has authored 11 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Neurology, 4 papers in Epidemiology and 3 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Andrew D. Monk's work include Traumatic Brain Injury and Neurovascular Disturbances (5 papers), Acute Ischemic Stroke Management (4 papers) and CAR-T cell therapy research (3 papers). Andrew D. Monk is often cited by papers focused on Traumatic Brain Injury and Neurovascular Disturbances (5 papers), Acute Ischemic Stroke Management (4 papers) and CAR-T cell therapy research (3 papers). Andrew D. Monk collaborates with scholars based in United States, Portugal and United Kingdom. Andrew D. Monk's co-authors include Sarah LaRose, Henrikas Vaitkevicius, Karen Li, Caron A. Jacobson, Daniel B. Rubin, Lauren Spendley, Ali Basil Ali, Can Ozan Tan, Farzaneh A. Sorond and Timothy R. Smith and has published in prestigious journals such as Brain, Neurology and Stroke.

In The Last Decade

Andrew D. Monk

10 papers receiving 390 citations

Peers

Andrew D. Monk

ONCOL

NEURO

BE

EEE

PRM

Sarah LaRose United States

Hedieh Khalatbari United States

Perrine Devic France

Frank Y. Lin United States

Takashi Yamamoto Japan

Shuichi Yamada Japan

Peter J. Madsen United States

Laura Baldassari United States

Aaron Victor United States

Meghan E. Munger United States

Sarah LaRose United States

Andrew D. Monk

225 ×1.0

ONCOL

200 ×1.7

NEURO

116 ×1.0

BE

85 ×1.0

EEE

68 ×1.2

PRM

Citations per year, relative to Andrew D. Monk Andrew D. Monk (= 1×) peers Sarah LaRose

Countries citing papers authored by Andrew D. Monk

Since Specialization

Citations

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

Fields of papers citing papers by Andrew D. Monk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew D. Monk. 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 Andrew D. Monk. The network helps show where Andrew D. Monk may publish in the future.

Co-authorship network of co-authors of Andrew D. Monk

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

All Works

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11 of 11 papers shown

1.

Regenhardt, Robert W., Neal M. Nolan, Alvin S. Das, et al.. (2024). Transcranial Doppler cerebrovascular reactivity: Thresholds for clinical significance in cerebrovascular disease. Journal of Neuroimaging. 34(3). 348–355.

2.

Holroyd, Kathryn B., Daniel B. Rubin, Sarah LaRose, et al.. (2021). Use of Transcranial Doppler as a Biomarker of CAR T Cell–Related Neurotoxicity. Neurology Clinical Practice. 12(1). 22–28. 1 indexed citations

3.

Wu, Kuan-Cheng, John Sunwoo, Faheem Sheriff, et al.. (2021). Validation of diffuse correlation spectroscopy measures of critical closing pressure against transcranial Doppler ultrasound in stroke patients. Journal of Biomedical Optics. 26(3). 26 indexed citations

4.

Das, Alvin S., Robert W. Regenhardt, Sarah LaRose, et al.. (2020). Microembolic Signals Detected by Transcranial Doppler Predict Future Stroke and Poor Outcomes. Journal of Neuroimaging. 30(6). 882–889. 6 indexed citations

5.

Sheriff, Faheem, Pedro Castro, Mariel G. Kozberg, et al.. (2020). Dynamic Cerebral Autoregulation Post Endovascular Thrombectomy in Acute Ischemic Stroke. Brain Sciences. 10(9). 641–641. 22 indexed citations

6.

Rubin, Daniel B., Karen Li, Sarah LaRose, et al.. (2020). Clinical Predictors of Neurotoxicity After Chimeric Antigen Receptor T-Cell Therapy. JAMA Neurology. 77(12). 1536–1536. 78 indexed citations

7.

Rubin, Daniel B., Husain Danish, Ali Basil Ali, et al.. (2019). Neurological toxicities associated with chimeric antigen receptor T-cell therapy. Brain. 142(5). 1334–1348. 169 indexed citations

8.

Sheriff, Faheem, Ayaz Khawaja, Farzaneh A. Sorond, et al.. (2019). Microemboli After Successful Thrombectomy Do Not Affect Outcome but Predict New Embolic Events. Stroke. 51(1). 154–161. 12 indexed citations

9.

Wu, Kuan-Cheng, Parisa Farzam, Faheem Sheriff, et al.. (2019). Critical Closing Pressure Measured in Stroke Patients with Diffuse Correlation Spectroscopy and Transcranial Doppler Ultrasound. 106. BW4A.4–BW4A.4. 1 indexed citations

10.

Petersen, Nils, Amir A. Zamani, Rose Du, et al.. (2016). Pathophysiologic differences in cerebral autoregulation after subarachnoid hemorrhage. Neurology. 86(21). 1950–1956. 53 indexed citations

11.

Sorond, Farzaneh A., Can Ozan Tan, Sarah LaRose, et al.. (2015). Deferoxamine, Cerebrovascular Hemodynamics, and Vascular Aging. Stroke. 46(9). 2576–2583. 25 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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