Ray Dorsey

983 total citations · 1 hit paper
6 papers, 266 citations indexed

About

Ray Dorsey is a scholar working on Neurology, Cellular and Molecular Neuroscience and General Health Professions. According to data from OpenAlex, Ray Dorsey has authored 6 papers receiving a total of 266 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Neurology, 2 papers in Cellular and Molecular Neuroscience and 1 paper in General Health Professions. Recurrent topics in Ray Dorsey's work include Parkinson's Disease Mechanisms and Treatments (5 papers), Neurological disorders and treatments (4 papers) and Genetic Neurodegenerative Diseases (2 papers). Ray Dorsey is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (5 papers), Neurological disorders and treatments (4 papers) and Genetic Neurodegenerative Diseases (2 papers). Ray Dorsey collaborates with scholars based in United States, United Kingdom and Netherlands. Ray Dorsey's co-authors include Yuzhe Yang, Christopher G. Tarolli, Mithri R. Junna, Dina Katabi, Hao Wang, Terry D. Ellis, Yuan Yuan, Daniel Crepeau, Melissa C. Lipford and Ying-Cong Chen and has published in prestigious journals such as Nature Medicine, SHILAP Revista de lepidopterología and Sensors.

In The Last Decade

Ray Dorsey

6 papers receiving 263 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.

Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals

2022 160 citations Yuzhe Yang, Yuan Yuan et al. Nature Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ray Dorsey United States	5	119	55	42	39	31	6	266
Michael Kelley Erb United States	6	148 1.2×	69 1.3×	40 1.0×	33 0.8×	22 0.7×	9	318
Mithri R. Junna United States	9	90 0.8×	49 0.9×	84 2.0×	87 2.2×	21 0.7×	20	324
Lauren Bataille United States	6	228 1.9×	117 2.1×	49 1.2×	45 1.2×	20 0.6×	7	415
Nikhil Mahadevan United States	8	95 0.8×	102 1.9×	31 0.7×	25 0.6×	18 0.6×	8	290
Bryan Ho United States	8	215 1.8×	65 1.2×	50 1.2×	48 1.2×	23 0.7×	14	317
Yauhen Statsenko United Arab Emirates	10	40 0.3×	26 0.5×	27 0.6×	69 1.8×	21 0.7×	61	387
Antti-Pekka Elomaa Finland	12	39 0.3×	72 1.3×	20 0.5×	17 0.4×	14 0.5×	31	312
Enrico Pellegrini United Kingdom	12	28 0.2×	25 0.5×	43 1.0×	41 1.1×	34 1.1×	21	582
Shira Hahn United States	8	90 0.8×	28 0.5×	77 1.8×	65 1.7×	11 0.4×	12	406
D. Cheng United States	7	16 0.1×	62 1.1×	62 1.5×	17 0.4×	30 1.0×	10	389

Countries citing papers authored by Ray Dorsey

Since Specialization

Citations

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

Fields of papers citing papers by Ray Dorsey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ray Dorsey

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

All Works

Sort: Min cites: Since: Top N: Style:

6 of 6 papers shown

1.

Johnson, Shane, Joan Severson, Ray Dorsey, et al.. (2024). Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson’s Disease. Sensors. 24(17). 5637–5637. 4 indexed citations

2.

Yang, Yuzhe, Yuan Yuan, Guo Zhang, et al.. (2022). Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals. Nature Medicine. 28(10). 2207–2215. 160 indexed citations breakdown →

3.

Dorsey, Ray, et al.. (2021). Digital Endpoints: Definition, Benefits, and Current Barriers in Accelerating Development and Adoption. SHILAP Revista de lepidopterología. 5(3). 216–223. 25 indexed citations

4.

Radder, Danique L. M., Nienke M. de Vries, Niels P. Riksen, et al.. (2018). Multidisciplinary care for people with Parkinson’s disease: the new kids on the block!. Expert Review of Neurotherapeutics. 19(2). 145–157. 49 indexed citations

5.

Dinesh, Karthik, Mulin Xiong, Jamie Adams, Ray Dorsey, & Gaurav Sharma. (2016). Signal analysis for detecting motor symptoms in Parkinson's and Huntington's disease using multiple body-affixed sensors: A pilot study. 1–5. 17 indexed citations

6.

Dorsey, Ray, Kevin Biglan, Shirley Eberly, et al.. (2011). Use of Tetrabenazine in Huntington Disease Patients on Antidepressants or with Advanced Disease: Results from the TETRA-HD Study. PLoS Currents. 3. RRN1283–RRN1283. 11 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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