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Federica Amato
Also published under:
Affiliation
Department of Control and Computer Engineering, Polytechnic University of Turin, Turin, Italy
Topic
Binary Classification,Machine Learning,Audio Recordings,Chaotic System,Feature Subset,K-nearest Neighbor,Learning Algorithms,Mel-frequency Cepstral Coefficients,Phase Space,Phase Space Reconstruction,Support Vector Machine,Vocal Fold,3D Geometry,Adjacent Windows,Body Fat,Body Mass Index,Concordance Correlation Coefficient,Convolutional Neural Network,Correlation-based Feature Selection,Customer Characteristics,Decision Support System,Detection Of The Presence,Disease Stage,Dynamic Conditions,Dysphonia,E Della,Early Parkinson’s Disease,Eating Disorders,Expert Decision,Expert System,F1 Score,Face Area,Feature Importance Analysis,Feature Selection Procedure,Female Subgroup,Finger Joints,Flex Sensors,Gastroesophageal Reflux Disease,General Power,Global Score,Good Sleep,Good Sleep Quality,Gradient Boosting,Hand Movements,Hand Opening,Healthy Control Subjects,Healthy Subjects,Hoarseness,Influence Of Obesity,Intraclass Correlation Coefficient,
Biography
Federica Amato received the B.S. and M.Sc. degrees in biomedical engineering from the Politecnico di Torino, Italy, in 2017 and 2020, respectively, where she is currently pursuing the Ph.D. degree with the Department of Control and Computer Engineering. From 2018 to 2019, she studied at the University of Cork, Ireland. Her M.Sc. degree discussing a thesis on the automatic assessment of Parkinson’s Disease (PD) by means of speech analysis. Her research interests include speech processing with a particular focus on early diagnosis of vocal disturbances in PD patients. Her research studies focus on automated speech analysis for remote PD monitoring and early diagnosis of speech disturbances.