Federica Amato

422 total citations
15 papers, 227 citations indexed

About

Federica Amato is a scholar working on Physiology, Neurology and Artificial Intelligence. According to data from OpenAlex, Federica Amato has authored 15 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Physiology, 4 papers in Neurology and 4 papers in Artificial Intelligence. Recurrent topics in Federica Amato's work include Voice and Speech Disorders (7 papers), Parkinson's Disease Mechanisms and Treatments (4 papers) and Speech Recognition and Synthesis (3 papers). Federica Amato is often cited by papers focused on Voice and Speech Disorders (7 papers), Parkinson's Disease Mechanisms and Treatments (4 papers) and Speech Recognition and Synthesis (3 papers). Federica Amato collaborates with scholars based in Italy, Uzbekistan and Germany. Federica Amato's co-authors include Gabriella Olmo, Luigi Borzì, Giovanni Saggio, Giovanni Costantini, Juan Rafael Orozco‐Arroyave, Luis Gascó, Luis Sigcha, Pietro Leo, Francesco Asci and Antonio Suppa and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Sensors.

In The Last Decade

Federica Amato

14 papers receiving 220 citations

Peers

Federica Amato
Kang Ren China
Federica Amato
Citations per year, relative to Federica Amato Federica Amato (= 1×) peers Kang Ren

Countries citing papers authored by Federica Amato

Since Specialization
Citations

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

Fields of papers citing papers by Federica Amato

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Federica Amato

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

All Works

15 of 15 papers shown
1.
Amato, Federica, et al.. (2024). Beyond breathalyzers: AI-powered speech analysis for alcohol intoxication detection. Expert Systems with Applications. 262. 125656–125656. 1 indexed citations
3.
Spinato, Giacomo, Federica Amato, Adolfo Di Fiore, et al.. (2024). Oral Care in Head and Neck Radiotherapy: Proposal for an Oral Hygiene Protocol. Journal of Personalized Medicine. 14(9). 1013–1013. 1 indexed citations
4.
Amato, Federica, et al.. (2023). Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey. Expert Systems with Applications. 219. 119651–119651. 20 indexed citations
5.
Costantini, Giovanni, Pietro Leo, Federica Amato, et al.. (2023). Artificial Intelligence-Based Voice Assessment of Patients with Parkinson’s Disease Off and On Treatment: Machine vs. Deep-Learning Comparison. Sensors. 23(4). 2293–2293. 41 indexed citations
6.
Amato, Federica, Gabriella Olmo, Francesco Asci, et al.. (2023). Robust and language-independent acoustic features in Parkinson's disease. Frontiers in Neurology. 14. 1198058–1198058. 6 indexed citations
7.
Sigcha, Luis, et al.. (2023). Deep learning and wearable sensors for the diagnosis and monitoring of Parkinson’s disease: A systematic review. Expert Systems with Applications. 229. 120541–120541. 62 indexed citations
8.
Imbalzano, Gabriele, Domiziana Rinaldi, Giovanna Calandra–Buonaura, et al.. (2022). How resistant are levodopa‐resistant axial symptoms? Response of freezing, posture, and voice to increasing levodopa intestinal infusion rates in Parkinson disease. European Journal of Neurology. 30(1). 96–106. 8 indexed citations
9.
Amato, Federica, et al.. (2022). Sleep Quality through Vocal Analysis: a Telemedicine Application. 706–711. 5 indexed citations
10.
Amato, Federica, et al.. (2022). Obesity and Gastro-Esophageal Reflux voice disorders: a Machine Learning approach. Cineca Institutional Research Information System (Tor Vergata University). 8. 1–6. 3 indexed citations
11.
Amato, Federica, et al.. (2021). Socially Assistive Robotics combined with Artificial Intelligence for ADHD. 1–6. 13 indexed citations
12.
Amato, Federica, Luigi Borzì, Gabriella Olmo, & Juan Rafael Orozco‐Arroyave. (2021). An algorithm for Parkinson’s disease speech classification based on isolated words analysis. Health Information Science and Systems. 9(1). 32–32. 37 indexed citations
13.
Amato, Federica, Luigi Borzì, Gabriella Olmo, et al.. (2021). Speech Impairment in Parkinson’s Disease: Acoustic Analysis of Unvoiced Consonants in Italian Native Speakers. IEEE Access. 9. 166370–166381. 13 indexed citations
14.
Borzì, Luigi, et al.. (2020). Smartphone-Based Evaluation of Postural Stability in Parkinson’s Disease Patients During Quiet Stance. Electronics. 9(6). 919–919. 14 indexed citations
15.
Amato, Federica, et al.. (2020). The Therapeutic Use of Humanoid Robots for Behavioral Disorders. 1–3. 3 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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