Dawn C. Matthews

1.7k total citations · 1 hit paper
25 papers, 872 citations indexed

About

Dawn C. Matthews is a scholar working on Psychiatry and Mental health, Physiology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Dawn C. Matthews has authored 25 papers receiving a total of 872 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Psychiatry and Mental health, 9 papers in Physiology and 8 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Dawn C. Matthews's work include Dementia and Cognitive Impairment Research (10 papers), Alzheimer's disease research and treatments (7 papers) and Medical Imaging Techniques and Applications (4 papers). Dawn C. Matthews is often cited by papers focused on Dementia and Cognitive Impairment Research (10 papers), Alzheimer's disease research and treatments (7 papers) and Medical Imaging Techniques and Applications (4 papers). Dawn C. Matthews collaborates with scholars based in United States, Belgium and United Kingdom. Dawn C. Matthews's co-authors include Lisa Mosconi, Mony J. de Leon, Richard Isaacson, Randolph D. Andrews, Randolph Andrews, Ricardo S. Osorio, Valentina Berti, Ana Lukić, Michelle Walters and Crystal Quinn and has published in prestigious journals such as PLoS ONE, Neurology and Scientific Reports.

In The Last Decade

Dawn C. Matthews

18 papers receiving 860 citations

Hit Papers

align trajectories

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.

Menopause impacts human brain structure, connectivity, energy metabolism, and amyloid-beta deposition

2021 140 citations Lisa Mosconi, Valentina Berti et al. Scientific Reports profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dawn C. Matthews United States	13	396	279	257	124	111	25	872
Zuo-Teng Wang China	15	319 0.8×	114 0.4×	293 1.1×	29 0.2×	88 0.8×	44	883
J.J. Himali United States	3	268 0.7×	131 0.5×	295 1.1×	39 0.3×	96 0.9×	3	839
Ross Carne Australia	11	274 0.7×	86 0.3×	523 2.0×	138 1.1×	148 1.3×	18	1.2k
Frank Hentschel Germany	19	309 0.8×	57 0.2×	256 1.0×	121 1.0×	114 1.0×	72	1.1k
John Murray United States	16	584 1.5×	229 0.8×	281 1.1×	27 0.2×	81 0.7×	21	918
Antonietta Fava Italy	16	381 1.0×	118 0.4×	189 0.7×	193 1.6×	34 0.3×	26	988
Chung‐Kai Sun United States	12	608 1.5×	65 0.2×	602 2.3×	70 0.6×	71 0.6×	28	1.1k
Brandalyn C. Riedel United States	6	220 0.6×	46 0.2×	149 0.6×	63 0.5×	41 0.4×	11	530
Auttawut Roontiva United States	9	517 1.3×	62 0.2×	463 1.8×	25 0.2×	134 1.2×	16	833
Yi Xing China	18	212 0.5×	35 0.1×	189 0.7×	52 0.4×	66 0.6×	52	758

Countries citing papers authored by Dawn C. Matthews

Since Specialization

Citations

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

Fields of papers citing papers by Dawn C. Matthews

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dawn C. Matthews. 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 Dawn C. Matthews. The network helps show where Dawn C. Matthews may publish in the future.

Co-authorship network of co-authors of Dawn C. Matthews

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

All Works

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20 of 20 papers shown

Williams, Steven, Caroline Andy, Steven Jett, et al.. (2025). Sex-specific associations of serum testosterone with gray matter volume and cerebral blood flow in midlife individuals at risk for Alzheimer’s disease. PLoS ONE. 20(1). e0317303–e0317303.

Kim, Su Jin, Mark E. Schmidt, Mark Slifstein, et al.. (2025). EC ₅₀ images reveal reproducible spatial variation in drug affinity across single- and repeat-dose occupancy studies. Journal of Cerebral Blood Flow & Metabolism. 45(11). 2233–2244.

Hernandez, Gerson D., et al.. (2023). Development of a selective estrogen β‐receptor phytoestrogen formulation – PhytoSERM – for the reduction of Alzheimer’s risk and relief of menopausal symptoms in women: a phase 2 randomized clinical trial framework. Alzheimer s & Dementia. 19(S21).

Singh, Baldev, et al.. (2023). Digital health and inpatient palliative care: a cohort-controlled study. BMJ Supportive & Palliative Care. 14(e1). e545–e548. 2 indexed citations

Ahmed, Kamran, et al.. (2023). GP assessment of unmet need in a complex multimorbid population using a data-driven and clinical triage system: a prospective cohort study. BJGP Open. 7(4). BJGPO.2023.0078–BJGPO.2023.0078. 3 indexed citations

Smith, Anne M., Nancy A. Obuchowski, Norman L. Foster, et al.. (2022). The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification. Journal of Nuclear Medicine. 64(2). 294–303. 15 indexed citations

Mosconi, Lisa, Valentina Berti, Jonathan P. Dyke, et al.. (2021). Menopause impacts human brain structure, connectivity, energy metabolism, and amyloid-beta deposition. Scientific Reports. 11(1). 10867–10867. 140 indexed citations breakdown →

Rahman, Aneela, Eva Schelbaum, Eric A. Hoffman, et al.. (2020). Sex-driven modifiers of Alzheimer risk. Neurology. 95(2). e166–e178. 104 indexed citations

Matthews, Dawn C., Aaron Ritter, Ronald G. Thomas, et al.. (2020). The Effects of Rasagiline on Glucose Metabolism and Cognition and Their Relationship to Tau Burden in a Double-Blind, Placebo-Controlled Phase Ii Clinical Trial of Participants with Alzheimer's Dementia. SSRN Electronic Journal. 2 indexed citations

10.

Rafii, Michael S., Michael Donohue, Dawn C. Matthews, et al.. (2019). Plasma Neurofilament Light and Alzheimer’s Disease Biomarkers in Down Syndrome: Results from the Down Syndrome Biomarker Initiative (DSBI). Journal of Alzheimer s Disease. 70(1). 131–138. 16 indexed citations

11.

Walters, Michelle, Crystal Quinn, Christine A. Ganzer, et al.. (2018). Associations of lifestyle and vascular risk factors with Alzheimer’s brain biomarker changes during middle age: a 3-year longitudinal study in the broader New York City area. BMJ Open. 8(11). e023664–e023664. 34 indexed citations

12.

Matthews, Dawn C., Hedva Lerman, Ana Lukić, et al.. (2018). FDG PET Parkinson’s disease-related pattern as a biomarker for clinical trials in early stage disease. NeuroImage Clinical. 20. 572–579. 64 indexed citations

13.

Lukić, Ana, Randolph D. Andrews, Viktoriya Bourakova, Gil D. Rabinovici, & Dawn C. Matthews. (2018). O4‐09‐06: MRI, FDG, AND EARLY FRAME AMYLOID IMAGE CLASSIFIERS TO CHARACTERIZE AND DIFFERENTIATE ALZHEIMER'S DISEASE VARIANTS AND NON‐AD DEMENTIAS. Alzheimer s & Dementia. 14(7S_Part_27). 1 indexed citations

14.

Mosconi, Lisa, Michelle Walters, Crystal Quinn, et al.. (2018). Lifestyle and vascular risk effects on MRI-based biomarkers of Alzheimer’s disease: a cross-sectional study of middle-aged adults from the broader New York City area. BMJ Open. 8(3). e019362–e019362. 65 indexed citations

15.

Rafii, Michael S., Ana Lukić, Randolph D. Andrews, et al.. (2017). PET Imaging of Tau Pathology and Relationship to Amyloid, Longitudinal MRI, and Cognitive Change in Down Syndrome: Results from the Down Syndrome Biomarker Initiative (DSBI). Journal of Alzheimer s Disease. 60(2). 439–450. 65 indexed citations

16.

Matthews, Dawn C., Ana Lukić, Randolph D. Andrews, et al.. (2016). Dissociation of Down syndrome and Alzheimer's disease effects with imaging. Alzheimer s & Dementia Translational Research & Clinical Interventions. 2(2). 69–81. 39 indexed citations

17.

Matthews, Dawn C., Michelle Davies, John Murray, et al.. (2014). Physical Activity, Mediterranean Diet and Biomarkers-Assessed Risk of Alzheimer’s: A Multi-Modality Brain Imaging Study. PubMed. 4(4). 43–57. 51 indexed citations

18.

Gordon, Mark Forrest, Thomas A. Comery, Igor D. Grachev, et al.. (2013). The Coalition Against Major Diseases: Dopamine Transporter Neuroimaging as an Enrichment Biomarker To Enable Parkinson's Disease Clinical Trials (P06.049). Neurology. 80(7_supplement). 1 indexed citations

19.

Matthews, Dawn C., Randolph D. Andrews, Lisa Mosconi, & Mark E. Schmidt. (2012). O3‐12‐02: When an amyloid PET threshold of 1.5 becomes 1.4 and longitudinal accumulation is not what it appears: Interpreting and reconciling values amidst scanner variability. Alzheimer s & Dementia. 8(4S_Part_12).

20.

Matthews, Dawn C., Randolph D. Andrews, Lisa Mosconi, & Mark E. Schmidt. (2012). IC‐P‐066: When an amyloid PET threshold of 1.5 becomes 1.4 and longitudinal accumulation is not what it appears: Interpreting and reconciling values amidst scanner variability. Alzheimer s & Dementia. 8(4S_Part_1).

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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