Leonardo Almeida

2.8k total citations
91 papers, 1.3k citations indexed

About

Leonardo Almeida is a scholar working on Neurology, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Leonardo Almeida has authored 91 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Neurology, 38 papers in Cellular and Molecular Neuroscience and 7 papers in Neurology. Recurrent topics in Leonardo Almeida's work include Neurological disorders and treatments (61 papers), Parkinson's Disease Mechanisms and Treatments (55 papers) and Genetic Neurodegenerative Diseases (21 papers). Leonardo Almeida is often cited by papers focused on Neurological disorders and treatments (61 papers), Parkinson's Disease Mechanisms and Treatments (55 papers) and Genetic Neurodegenerative Diseases (21 papers). Leonardo Almeida collaborates with scholars based in United States, Japan and Brazil. Leonardo Almeida's co-authors include Michael S. Okun, Kelly D. Foote, Joshua K. Wong, Robert S. Eisinger, Daniel Martínez-Ramírez, Adolfo Ramirez–Zamora, Christopher W. Hess, Erik H. Middlebrooks, Aysegul Gunduz and Aparna Wagle Shukla and has published in prestigious journals such as SHILAP Revista de lepidopterología, Brain and Neurology.

In The Last Decade

Leonardo Almeida

83 papers receiving 1.3k citations

Peers

Leonardo Almeida
Leonardo Almeida
Citations per year, relative to Leonardo Almeida Leonardo Almeida (= 1×) peers David J. Pedrosa

Countries citing papers authored by Leonardo Almeida

Since Specialization
Citations

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

Fields of papers citing papers by Leonardo Almeida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leonardo Almeida

This figure shows the co-authorship network connecting the top 25 collaborators of Leonardo Almeida. A scholar is included among the top collaborators of Leonardo Almeida 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 Leonardo Almeida. Leonardo Almeida 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.
Almeida, Leonardo, et al.. (2025). Efficient training: Federated learning cost analysis. Big Data Research. 40. 100510–100510. 2 indexed citations
2.
Almeida, Leonardo, et al.. (2025). Beyond performance comparing the costs of applying Deep and Shallow Learning. Computer Communications. 243. 108312–108312.
3.
Stanslaski, Scott, Rebekah L. S. Summers, Lisa Tonder, et al.. (2024). Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) clinical trial. npj Parkinson s Disease. 10(1). 174–174. 26 indexed citations
4.
Cagle, Jackson, Kara A. Johnson, Leonardo Almeida, et al.. (2023). Brain Recording Analysis and Visualization Online (BRAVO): An open-source visualization tool for deep brain stimulation data. Brain stimulation. 16(3). 793–797. 6 indexed citations
5.
Wong, Joshua K., Wei Hu, Jon B. Toledo, et al.. (2023). Double blind, nonrandomized crossover study of active recharge biphasic deep brain stimulation for primary dystonia. Parkinsonism & Related Disorders. 109. 105328–105328. 1 indexed citations
6.
Marsili, Luca, Elizabeth G. Keeling, Maria Fiorella Contarino, et al.. (2022). Functional Movement Disorders and Deep Brain Stimulation: A Multi‐Center Study. Movement Disorders Clinical Practice. 10(1). 94–100. 6 indexed citations
7.
Nguyen, Oliver T., et al.. (2021). Geospatial Analysis of Persons with Movement Disorders Living in Underserved Regions. Tremor and Other Hyperkinetic Movements. 11(1). 34–34. 7 indexed citations
8.
Patel, Bhavana, Shannon Chiu, Joshua K. Wong, et al.. (2021). Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology. Expert Review of Medical Devices. 18(9). 875–891. 9 indexed citations
9.
Johnson, Kara A., Daria Nesterovich Anderson, Jill L. Ostrem, et al.. (2020). Structural connectivity predicts clinical outcomes of deep brain stimulation for Tourette syndrome. Brain. 143(8). 2607–2623. 45 indexed citations
10.
Okromelidze, Lela, Takashi Tsuboi, Robert S. Eisinger, et al.. (2020). Functional and Structural Connectivity Patterns Associated with Clinical Outcomes in Deep Brain Stimulation of the Globus Pallidus Internus for Generalized Dystonia. American Journal of Neuroradiology. 41(3). 508–514. 35 indexed citations
11.
Cernera, Stephanie, Robert S. Eisinger, Joshua K. Wong, et al.. (2020). Long-term Parkinson’s disease quality of life after staged DBS: STN vs GPi and first vs second lead. npj Parkinson s Disease. 6(1). 13–13. 20 indexed citations
12.
Opri, Enrico, Stephanie Cernera, Rene Molina, et al.. (2020). Chronic embedded cortico-thalamic closed-loop deep brain stimulation for the treatment of essential tremor. Science Translational Medicine. 12(572). 91 indexed citations
13.
Middlebrooks, Erik H., Ricardo A. Domingo, Tito Vivas-Buitrago, et al.. (2020). Neuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain Connectomics. American Journal of Neuroradiology. 41(9). 1558–1568. 67 indexed citations
14.
Middlebrooks, Erik H., İbrahim Sacit Tuna, Sanjeet S. Grewal, et al.. (2018). Segmentation of the Globus Pallidus Internus Using Probabilistic Diffusion Tractography for Deep Brain Stimulation Targeting in Parkinson Disease. American Journal of Neuroradiology. 39(6). 1127–1134. 36 indexed citations
15.
Almeida, Leonardo, Daniel Martínez-Ramírez, Bilal Ahmed, et al.. (2017). A pilot trial of square biphasic pulse deep brain stimulation for dystonia: The BIP dystonia study. Movement Disorders. 32(4). 615–618. 15 indexed citations
16.
Jesus, Sol De, Leonardo Almeida, Leili Shahgholi, et al.. (2017). Square biphasic pulse deep brain stimulation for essential tremor: The BiP tremor study. Parkinsonism & Related Disorders. 46. 41–46. 20 indexed citations
17.
Almeida, Leonardo, Bilal Ahmed, Roger Walz, et al.. (2016). Depressive Symptoms are Frequent in Atypical Parkinsonian Disorders. Movement Disorders Clinical Practice. 4(2). 191–197. 25 indexed citations
18.
Almeida, Leonardo, Benjamin J. Ditty, He Huang, et al.. (2016). Deep Brain Stimulation Battery Longevity: Comparison of Monopolar Versus Bipolar Stimulation Modes. Movement Disorders Clinical Practice. 3(4). 359–366. 25 indexed citations
19.
Almeida, Leonardo, et al.. (2014). Shorter Pulse Generator Longevity and More Frequent Stimulator Adjustments With Pallidal DBS for Dystonia Versus Other Movement Disorders. Brain stimulation. 7(3). 345–349. 21 indexed citations
20.
Kleefstra, Tjitske, Trevor Wood, Leonardo Almeida, et al.. (2005). High prevalence of SLC6A8 deficiency, a novel X-linked mental retardation syndrome. Molecular Genetics and Metabolism. 84(3). 204–204. 1 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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