David Mann

56.9k total citations · 9 hit papers
332 papers, 21.3k citations indexed

About

David Mann is a scholar working on Physiology, Neurology and General Health Professions. According to data from OpenAlex, David Mann has authored 332 papers receiving a total of 21.3k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Physiology, 73 papers in Neurology and 57 papers in General Health Professions. Recurrent topics in David Mann's work include Alzheimer's disease research and treatments (76 papers), Amyotrophic Lateral Sclerosis Research (49 papers) and Parkinson's Disease Mechanisms and Treatments (43 papers). David Mann is often cited by papers focused on Alzheimer's disease research and treatments (76 papers), Amyotrophic Lateral Sclerosis Research (49 papers) and Parkinson's Disease Mechanisms and Treatments (43 papers). David Mann collaborates with scholars based in United States, United Kingdom and Japan. David Mann's co-authors include Julie S. Snowden, David Neary, P. O. Yates, Erkki Ruoslahti, Yu Yamaguchi, Masato Hasegawa, Haruhiko Akiyama, Tetsuaki Arai, Takashi Nonaka and Oded Nov and has published in prestigious journals such as Nature, New England Journal of Medicine and Journal of Biological Chemistry.

In The Last Decade

David Mann

314 papers receiving 20.8k citations

Hit Papers

TDP-43 is a component of ubiquitin-positive tau-... 1990 2026 2002 2014 2006 1990 2020 2013 2013 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. TDP-43 is a component of ubiquitin-positive tau-negative inclusions in frontotemporal lobar degeneration and amyotrophic lateral sclerosis
    2006 2.1k citations David Mann et al. profile →
  2. Negative regulation of transforming growth factor-β by the proteoglycan decorin
    1990 1.3k citations David Mann et al. profile →
  3. COVID-19 transforms health care through telemedicine: Evidence from the field
    2020 955 citations David Mann, Rumi Chunara et al. Journal of the American Medical Informatics Association profile →
  4. Prion-like spreading of pathological α-synuclein in brain
    2013 639 citations David Mann et al. profile →
  5. Prion-like Properties of Pathological TDP-43 Aggregates from Diseased Brains
    2013 389 citations David Mann et al. profile →
  6. Evidence-Based Risk Communication
    2014 281 citations David Mann, David Feldstein et al. profile →
  7. A framework for digital health equity
    2022 240 citations Safiya Richardson, Katharine Lawrence et al. npj Digital Medicine profile →
  8. Wearable Health Technology and Electronic Health Record Integration: Scoping Review and Future Directions
    2019 228 citations Sara Chokshi, David Mann et al. profile →
  9. Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19
    2020 225 citations Rumi Chunara, Katharine Lawrence et al. Journal of the American Medical Informatics Association profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Mann United States 73 7.4k 6.0k 5.3k 2.5k 2.2k 332 21.3k
Valery L. Feigin New Zealand 69 7.9k 1.1× 1.7k 0.3× 4.0k 0.8× 3.5k 1.4× 1.7k 0.8× 286 33.1k
Fang Fang China 70 3.6k 0.5× 2.6k 0.4× 5.0k 0.9× 1.3k 0.5× 1000 0.4× 864 22.2k
William G. Johnson United States 54 6.7k 0.9× 3.0k 0.5× 3.2k 0.6× 1.9k 0.8× 4.2k 1.9× 239 16.3k
Yoav Ben‐Shlomo United Kingdom 88 9.6k 1.3× 3.6k 0.6× 1.8k 0.3× 1.9k 0.8× 3.1k 1.4× 531 26.7k
Gavin Giovannoni United Kingdom 79 7.2k 1.0× 1.5k 0.2× 4.3k 0.8× 2.2k 0.9× 2.0k 0.9× 678 26.2k
Christopher M. Clark United States 64 6.4k 0.9× 8.6k 1.4× 4.7k 0.9× 2.9k 1.2× 1.9k 0.9× 183 20.1k
David Schoenfeld United States 95 3.2k 0.4× 2.6k 0.4× 4.5k 0.8× 489 0.2× 990 0.4× 347 33.2k
Perminder S. Sachdev Australia 102 3.8k 0.5× 6.4k 1.1× 4.3k 0.8× 6.1k 2.5× 2.3k 1.0× 995 43.0k
Malcolm Macleod United Kingdom 62 2.2k 0.3× 1.8k 0.3× 3.6k 0.7× 2.8k 1.1× 1.4k 0.6× 232 18.4k
John Powell United Kingdom 63 2.2k 0.3× 2.5k 0.4× 4.3k 0.8× 970 0.4× 3.5k 1.6× 351 15.8k

Countries citing papers authored by David Mann

Since Specialization
Citations

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

Fields of papers citing papers by David Mann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Mann

This figure shows the co-authorship network connecting the top 25 collaborators of David Mann. A scholar is included among the top collaborators of David Mann 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 David Mann. David Mann 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
1.
Feldstein, David, Rachel Hess, David Mann, et al.. (2024). Snowball Group Usability Testing for Rapid and Iterative Multisite Tool Development: Method Development Study. JMIR Formative Research. 9. e55316–e55316.
2.
Andreadis, Katerina, et al.. (2024). Mixed methods assessment of the influence of demographics on medical advice of ChatGPT. Journal of the American Medical Informatics Association. 31(9). 2002–2009. 11 indexed citations
3.
Singh, Nina, et al.. (2024). Developing and Scaling Remote Patient Monitoring Capacity in Ambulatory Practice. NEJM Catalyst. 5(6). 3 indexed citations
4.
Stevens, Elizabeth R., et al.. (2024). Lightening the Load: Generative AI to Mitigate the Burden of the New Era of Obesity Medical Therapy. JMIR Diabetes. 9. e58680–e58680. 2 indexed citations
5.
Mandal, Soumik, Batia M. Wiesenfeld, David Mann, et al.. (2024). Quantifying the impact of telemedicine and patient medical advice request messages on physicians' work-outside-work. npj Digital Medicine. 7(1). 35–35. 8 indexed citations
6.
Nov, Oded, Nina Singh, & David Mann. (2023). Putting ChatGPT’s Medical Advice to the (Turing) Test: Survey Study. JMIR Medical Education. 9. e46939–e46939. 117 indexed citations
7.
Lawrence, Katharine, Nina Singh, Lisa Groom, et al.. (2023). Operational Implementation of Remote Patient Monitoring Within a Large Ambulatory Health System: Multimethod Qualitative Case Study. JMIR Human Factors. 10. e45166–e45166. 13 indexed citations
8.
Blecker, Saul, et al.. (2023). Leveraging Electronic Health Record Technology and Team Care to Address Medication Adherence: Protocol for a Cluster Randomized Controlled Trial. JMIR Research Protocols. 12. e47930–e47930. 4 indexed citations
9.
10.
Lawrence, Katharine, Oded Nov, David Mann, et al.. (2022). The Impact of Telemedicine on Physicians’ After-hours Electronic Health Record “Work Outside Work” During the COVID-19 Pandemic: Retrospective Cohort Study. JMIR Medical Informatics. 10(7). e34826–e34826. 12 indexed citations
11.
Richardson, Safiya, Jeffrey Solomon, Sundas Khan, et al.. (2022). Nudging Health Care Providers’ Adoption of Clinical Decision Support: Protocol for the User-Centered Development of a Behavioral Economics–Inspired Electronic Health Record Tool. JMIR Research Protocols. 12. e42653–e42653. 4 indexed citations
12.
Mandal, Soumik, Batia M. Wiesenfeld, David Mann, et al.. (2022). Evidence for Telemedicine’s Ongoing Transformation of Health Care Delivery Since the Onset of COVID-19: Retrospective Observational Study. JMIR Formative Research. 6(10). e38661–e38661. 14 indexed citations
13.
Austrian, Jonathan, Adam Szerencsy, Leora I. Horwitz, et al.. (2021). Applying A/B Testing to Clinical Decision Support: Rapid Randomized Controlled Trials. Journal of Medical Internet Research. 23(4). e16651–e16651. 29 indexed citations
14.
Akerman, Meredith, et al.. (2021). Application of telemedicine video visits in a maternal-fetal medicine practice at the epicenter of the COVID-19 pandemic. American Journal of Obstetrics & Gynecology MFM. 3(6). 100469–100469. 26 indexed citations
15.
Lawrence, Katharine, Donna Shelley, Hayley M. Belli, et al.. (2021). Effectiveness of an Integrated Engagement Support System to Facilitate Patient Use of Digital Diabetes Prevention Programs: Protocol for a Randomized Controlled Trial. JMIR Research Protocols. 10(2). e26750–e26750. 8 indexed citations
16.
Weerahandi, Himali, et al.. (2020). A Mobile Health Coaching Intervention for Controlling Hypertension: Single-Arm Pilot Pre-Post Study. JMIR Formative Research. 4(5). e13989–e13989. 16 indexed citations
17.
Richardson, Safiya, David Feldstein, Thomas McGinn, et al.. (2019). Live Usability Testing of Two Complex Clinical Decision Support Tools: Observational Study. JMIR Human Factors. 6(2). e12471–e12471. 12 indexed citations
18.
Mann, David, Diego Ponieman, Howard Leventhal, & Ethan A. Halm. (2009). Predictors of adherence to diabetes medications: the role of disease and medication beliefs. Journal of Behavioral Medicine. 32(3). 278–284. 225 indexed citations
19.
Mann, David & S. Natarajan. (2007). Inverse Relationship between Lipid-lowering Drugs and Saturated Fat Intake in US Adults. Cardiovascular Drugs and Therapy. 21(2). 109–115.
20.

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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