Francesco T. Mangano

4.6k total citations
155 papers, 2.9k citations indexed

About

Francesco T. Mangano is a scholar working on Psychiatry and Mental health, Cellular and Molecular Neuroscience and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Francesco T. Mangano has authored 155 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Psychiatry and Mental health, 56 papers in Cellular and Molecular Neuroscience and 56 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Francesco T. Mangano's work include Epilepsy research and treatment (63 papers), Cerebrospinal fluid and hydrocephalus (45 papers) and EEG and Brain-Computer Interfaces (39 papers). Francesco T. Mangano is often cited by papers focused on Epilepsy research and treatment (63 papers), Cerebrospinal fluid and hydrocephalus (45 papers) and EEG and Brain-Computer Interfaces (39 papers). Francesco T. Mangano collaborates with scholars based in United States, Canada and Israel. Francesco T. Mangano's co-authors include Hansel M. Greiner, Paul S. Horn, Ravindra Arya, Douglas F. Rose, Katherine D. Holland, Weihong Yuan, Blaise V. Jones, Hisako Fujiwara, Dean A. Hertzler and Tracy A. Glauser and has published in prestigious journals such as SHILAP Revista de lepidopterología, Development and Neurology.

In The Last Decade

Francesco T. Mangano

144 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francesco T. Mangano United States 29 1.1k 1.1k 936 892 488 155 2.9k
Vijay M. Thadani United States 28 1.8k 1.6× 1.2k 1.2× 793 0.8× 736 0.8× 493 1.0× 54 3.1k
William Harkness United Kingdom 34 1.9k 1.7× 1.1k 1.0× 1.3k 1.4× 780 0.9× 655 1.3× 84 3.9k
Matthew D. Smyth United States 31 533 0.5× 729 0.7× 637 0.7× 670 0.8× 347 0.7× 99 2.8k
Didier Scavarda France 29 1.2k 1.0× 765 0.7× 526 0.6× 903 1.0× 727 1.5× 112 2.8k
Matthew D. Smyth United States 35 614 0.5× 1.1k 1.1× 473 0.5× 1.1k 1.2× 653 1.3× 123 3.8k
Dileep Nair United States 36 2.0k 1.8× 1.6k 1.5× 779 0.8× 2.5k 2.8× 603 1.2× 94 4.3k
Nobuhiro Mikuni Japan 36 1.3k 1.1× 1.2k 1.1× 391 0.4× 1.8k 2.0× 1.4k 2.9× 270 4.6k
Shigeki Kameyama Japan 26 987 0.9× 744 0.7× 578 0.6× 730 0.8× 725 1.5× 112 2.6k
Keith G. Davies United States 29 1.6k 1.4× 929 0.9× 680 0.7× 1.0k 1.2× 322 0.7× 72 3.1k
Taketoshi Maehara Japan 27 961 0.8× 521 0.5× 486 0.5× 595 0.7× 497 1.0× 179 2.5k

Countries citing papers authored by Francesco T. Mangano

Since Specialization
Citations

This map shows the geographic impact of Francesco T. Mangano'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 Francesco T. Mangano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Francesco T. Mangano more than expected).

Fields of papers citing papers by Francesco T. Mangano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Francesco T. Mangano. 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 Francesco T. Mangano. The network helps show where Francesco T. Mangano may publish in the future.

Co-authorship network of co-authors of Francesco T. Mangano

This figure shows the co-authorship network connecting the top 25 collaborators of Francesco T. Mangano. A scholar is included among the top collaborators of Francesco T. Mangano 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 Francesco T. Mangano. Francesco T. Mangano 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
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Ritter, David M., Hansel M. Greiner, Jeffrey R. Tenney, et al.. (2025). Altered cortical excitability in tuberous sclerosis and the effect of mTOR inhibitors: An intracranial electrical stimulation study. Clinical Neurophysiology. 172. 1–9.
3.
Simon, Tamara D., Panteha Hayati Rezvan, Susan Coffin, et al.. (2024). Infection rates during eras of intrathecal antibiotic use followed by antibiotic-impregnated catheter use in prevention of cerebrospinal fluid shunt infection. Journal of Neurosurgery Pediatrics. 34(4). 357–364.
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Wissel, Benjamin D., Hansel M. Greiner, Tracy A. Glauser, et al.. (2024). Early Identification of Candidates for Epilepsy Surgery. Neurology. 102(4). e208048–e208048. 5 indexed citations
6.
Kronman, Matthew P., Kathryn B. Whitlock, Chuan Zhou, et al.. (2023). Associations of Standard Care, Intrathecal Antibiotics, and Antibiotic-Impregnated Catheters With Cerebrospinal Fluid Shunt Infection Organisms and Resistance. Journal of the Pediatric Infectious Diseases Society. 12(9). 504–512. 2 indexed citations
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Lindquist, Diana M., et al.. (2023). Early postnatal microglial ablation in the Ccdc39 mouse model reveals adverse effects on brain development and in neonatal hydrocephalus. Fluids and Barriers of the CNS. 20(1). 42–42. 5 indexed citations
9.
Dudley, Jonathan A., Usha D. Nagaraj, Stephanie L. Merhar, et al.. (2023). DTI of Opioid-Exposed Fetuses Using ComBat Harmonization: A Bi-Institutional Study. American Journal of Neuroradiology. 44(9). 1084–1089. 3 indexed citations
10.
Fujiwara, Hisako, Darren S. Kadis, Hansel M. Greiner, et al.. (2022). Clinical validation of magnetoencephalography network analysis for presurgical epilepsy evaluation. Clinical Neurophysiology. 142. 199–208. 5 indexed citations
11.
Mangano, Francesco T., et al.. (2022). International Pediatric Multidisciplinary Management Using Telemedicine to Promote Equitable Care. Telemedicine Journal and e-Health. 29(5). 674–685. 1 indexed citations
12.
Skoch, Jesse, Ravindra Arya, Katherine D. Holland, et al.. (2022). Comparison of outcomes after stereoelectroencephalography and subdural grid monitoring in pediatric tuberous sclerosis complex. Neurosurgical FOCUS. 53(4). E5–E5. 9 indexed citations
13.
Trout, Andrew T., Rupa Radhakrishnan, Paul S. Horn, et al.. (2021). Subtraction ictal SPECT co-registered to MRI (SISCOM) patterns in children with temporal lobe epilepsy. Epilepsy & Behavior. 121(Pt A). 108074–108074. 2 indexed citations
14.
Byars, Anna W., Paul S. Horn, Hansel M. Greiner, et al.. (2020). Neuropsychological outcomes after pediatric epilepsy surgery: Role of electrical stimulation language mapping. Seizure. 80. 183–191. 6 indexed citations
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Patel, Smruti, et al.. (2019). Not all ventriculomegaly is created equal: diagnostic overview of fetal, neonatal and pediatric ventriculomegaly. Child s Nervous System. 36(8). 1681–1696. 18 indexed citations
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Arya, Ravindra, James Leach, Paul S. Horn, et al.. (2016). Clinical factors predict surgical outcomes in pediatric MRI-negative drug-resistant epilepsy. Seizure. 41. 56–61. 19 indexed citations
18.
Greiner, Hansel M., Paul S. Horn, Ravindra Arya, et al.. (2014). Acute postoperative seizures and long-term outcome following pediatric epilepsy surgery. Seizure. 23(6). 483–486. 11 indexed citations
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Arya, Ravindra, et al.. (2013). Vagus nerve stimulation for medically refractory absence epilepsy. Seizure. 22(4). 267–270. 31 indexed citations
20.
Xiang, Jing, Yang Liu, Yingying Wang, et al.. (2009). Frequency and spatial characteristics of high‐frequency neuromagnetic signals in childhood epilepsy. Epileptic Disorders. 11(2). 113–125. 64 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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