Michelle Gee

6.3k total citations · 2 hit papers
26 papers, 3.8k citations indexed

About

Michelle Gee is a scholar working on Psychiatry and Mental health, Physiology and Pharmacology. According to data from OpenAlex, Michelle Gee has authored 26 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Psychiatry and Mental health, 10 papers in Physiology and 5 papers in Pharmacology. Recurrent topics in Michelle Gee's work include Alzheimer's disease research and treatments (7 papers), Dementia and Cognitive Impairment Research (6 papers) and Tryptophan and brain disorders (4 papers). Michelle Gee is often cited by papers focused on Alzheimer's disease research and treatments (7 papers), Dementia and Cognitive Impairment Research (6 papers) and Tryptophan and brain disorders (4 papers). Michelle Gee collaborates with scholars based in United Kingdom, United States and Japan. Michelle Gee's co-authors include Michael C. Irizarry, Michio Kanekiyo, Shobha Dhadda, Christopher H. van Dyck, Lynn D. Kramer, Chad J. Swanson, David Watson, Takeshi Iwatsubo, Paul Aisen and Randall J. Bateman and has published in prestigious journals such as New England Journal of Medicine, The Journal of Physiology and Annals of Neurology.

In The Last Decade

Michelle Gee

24 papers receiving 3.7k citations

Hit Papers

Lecanemab in Early Alzheimer’s Disease 2022 2026 2023 2024 2022 2024 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michelle Gee United Kingdom 17 1.7k 1.3k 763 554 525 26 3.8k
Lutz Froelich Germany 19 1.9k 1.1× 1.4k 1.0× 777 1.0× 569 1.0× 376 0.7× 54 3.9k
Marwan Sabbagh United States 9 1.9k 1.1× 1.2k 0.9× 731 1.0× 536 1.0× 310 0.6× 14 3.7k
Michio Kanekiyo United States 12 1.8k 1.1× 1.1k 0.8× 707 0.9× 534 1.0× 284 0.5× 28 3.3k
Madia Lozupone Italy 34 2.2k 1.3× 820 0.6× 700 0.9× 621 1.1× 289 0.6× 144 4.4k
Michael S. Rafii United States 33 1.7k 1.0× 1.3k 1.0× 979 1.3× 470 0.8× 410 0.8× 112 4.8k
Ana Frank Spain 34 1.9k 1.1× 1.2k 0.9× 956 1.3× 489 0.9× 389 0.7× 100 4.4k
Lynn D. Kramer United States 21 2.4k 1.4× 2.1k 1.5× 927 1.2× 765 1.4× 752 1.4× 64 5.0k
Howard Fillit United States 37 1.4k 0.8× 1.3k 0.9× 733 1.0× 374 0.7× 286 0.5× 124 4.2k
Chen‐Chen Tan China 31 1.6k 0.9× 1.4k 1.0× 1.0k 1.3× 412 0.7× 309 0.6× 115 4.6k
Vitaliy Ovod United States 19 2.9k 1.7× 1.5k 1.1× 940 1.2× 379 0.7× 522 1.0× 26 4.2k

Countries citing papers authored by Michelle Gee

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Gee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle Gee

This figure shows the co-authorship network connecting the top 25 collaborators of Michelle Gee. A scholar is included among the top collaborators of Michelle Gee 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 Michelle Gee. Michelle Gee 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.
Kanekiyo, Michio, et al.. (2025). The Lecanemab Clarity AD Open‐Label Extension in Early Alzheimer’s Disease: Initial Findings From the 48‐Month Analysis. Alzheimer s & Dementia. 21(S7). e108905–e108905.
2.
Sperling, Reisa, Keith A. Johnson, Shobha Dhadda, et al.. (2025). Long‐term safety and efficacy of lecanemab in early Alzheimer's disease: Results from the clarity AD open‐label extension study. Alzheimer s & Dementia. 21(12). e70905–e70905.
3.
Honig, Lawrence S., Marwan N. Sabbagh, Christopher H. van Dyck, et al.. (2024). Updated safety results from phase 3 lecanemab study in early Alzheimer’s disease. Alzheimer s Research & Therapy. 16(1). 105–105. 61 indexed citations breakdown →
4.
Cohen, Sarah, Christopher H. van Dyck, Michelle Gee, et al.. (2023). Lecanemab Clarity AD: Quality-of-Life Results from a Randomized, Double-Blind Phase 3 Trial in Early Alzheimer's Disease. The Journal of Prevention of Alzheimer s Disease. 10(4). 771–777. 50 indexed citations
6.
Dyck, Christopher H. van, Chad J. Swanson, Paul Aisen, et al.. (2022). Lecanemab in Early Alzheimer’s Disease. New England Journal of Medicine. 388(1). 9–21. 2741 indexed citations breakdown →
7.
Bullich, Santiago, André Mueller, Susan De Santi, et al.. (2022). Evaluation of tau deposition using 18F-PI-2620 PET in MCI and early AD subjects—a MissionAD tau sub-study. Alzheimer s Research & Therapy. 14(1). 105–105. 16 indexed citations
8.
Irizarry, Michael C., Shobha Dhadda, Michio Kanekiyo, et al.. (2021). Baseline characteristics for CLARITY AD: A phase 3 placebo‐controlled, double‐blind, parallel‐group, 18‐month study evaluating lecanemab (ban2401) in early Alzheimer's disease. Alzheimer s & Dementia. 17(S9). 2 indexed citations
9.
Caboral‐Stevens, Meriam, et al.. (2019). Effects of peer-mentoring on stress and anxiety levels of undergraduate nursing students: An integrative review. Journal of Professional Nursing. 36(4). 223–228. 71 indexed citations
11.
Lowe, Denise M., Michelle Gee, Carl Haslam, et al.. (2013). Lead Discovery for Human Kynurenine 3-Monooxygenase by High-Throughput RapidFire Mass Spectrometry. SLAS DISCOVERY. 19(4). 508–515. 31 indexed citations
12.
Rektor, Ivan, Gregory L. Krauss, Michal Bar, et al.. (2012). Perampanel Study 207: long-term open-label evaluation in patients with epilepsy. Acta Neurologica Scandinavica. 126(4). n/a–n/a. 66 indexed citations
14.
Hutchinson, Sue, Melanie Leveridge, Peter Francis, et al.. (2011). Enabling Lead Discovery for Histone Lysine Demethylases by High-Throughput RapidFire Mass Spectrometry. SLAS DISCOVERY. 17(1). 39–48. 72 indexed citations
15.
Hewett, K., W. Chrzanowski, Mark F. Schmitz, et al.. (2008). Eight-week, placebo-controlled, double-blind comparison of the antidepressant efficacy and tolerability of bupropion XR and venlafaxine XR. Journal of Psychopharmacology. 23(5). 531–538. 47 indexed citations
16.
Steiner, Meir, et al.. (2005). Luteal phase dosing with paroxetine controlled release (CR) in the treatment of premenstrual dysphoric disorder. American Journal of Obstetrics and Gynecology. 193(2). 352–360. 50 indexed citations
17.
Wagner, Karen Dineen, R.M.F. Berard, Murray B. Stein, et al.. (2004). A Multicenter, Randomized, Double-blind, Placebo-Controlled Trial ofParoxetine in Children and Adolescents With Social Anxiety Disorder. Archives of General Psychiatry. 61(11). 1153–1153. 153 indexed citations
18.
Gee, Michelle, et al.. (1999). The relationship between axonal spike shape and functional modality in cutaneous C-fibres in the pig and rat. Neuroscience. 90(2). 509–518. 20 indexed citations
19.
Gee, Michelle, et al.. (1997). The Relationship between Cutaneous C Fibre Type and Antidromic Vasodilatation in the Rabbit and the Rat. The Journal of Physiology. 503(1). 31–44. 41 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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