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Giovanna Sannino
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2020 – today
- 2025
- [j34]Naeem Ullah
, Javed Ali Khan
Explainable Artificial Intelligence: Importance, Use Domains, Stages, Output Shapes, and Challenges. ACM Comput. Surv. 57(4): 94:1-94:36 (2025) - 2024
- [j33]Raffaele Dubbioso
Precision medicine in ALS: Identification of new acoustic markers for dysarthria severity assessment. Biomed. Signal Process. Control. 89: 105706 (2024) - [c42]Vincenzo Bevilacqua
Cross-domain Super-Resolution in Medical Imaging. ISCC 2024: 1-6 - [c41]Pranita Subhash Shedage, Seyedamin Pouriyeh, Reza M. Parizi, Meng Han, Giovanna Sannino, Nasrin Dehbozorgi:
Stress Detection Using Multimodal Physiological Signals With Machine Learning From Wearable Devices. ISCC 2024: 1-6 - [c40]Naeem Ullah
Bridging Clinical Gaps: Multi-Dataset Integration for Reliable Multi-Class Lung Disease Classification with DeepCRINet and Occlusion Sensitivity. ISCC 2024: 1-6 - 2023
- [j32]Daniel Riccio
CNN-based classification of phonocardiograms using fractal techniques. Biomed. Signal Process. Control. 86(Part B): 105186 (2023) - [j31]Antonio Celesti
Special Issue "Advances in Machine and Deep Learning in the Health Domain". Comput. 12(7): 135 (2023) - [j30]Ivanoe De Falco
Classification of Covid-19 chest X-ray images by means of an interpretable evolutionary rule-based approach. Neural Comput. Appl. 35(22): 16061-16071 (2023) - [j29]Giovanna Sannino
Special Issue: "Intelligent Systems for Clinical Care and Remote Patient Monitoring". Sensors 23(18): 7993 (2023) - [c39]Antonio Celesti, Giovanna Sannino, Mario A. Bochicchio, Maria Fazio, Massimo Villari, Fabrizio Celesti
The Tele-Rehabilitaion as a Service (TRaaS) Project: Rationale, Study Design, and Methodology. e-Science 2023: 1-7 - [c38]Naeem Ullah
A Novel Deep Learning Approach for Colon and Lung Cancer Classification Using Histopathological Images. e-Science 2023: 1-10 - [i1]Fatemeh Mosaiyebzadeh, Seyedamin Pouriyeh, Reza M. Parizi, Quan Z. Sheng, Meng Han, Liang Zhao, Giovanna Sannino, Daniel Macêdo Batista:
Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey. CoRR abs/2303.14544 (2023) - 2022
- [j28]Ivanoe De Falco
A Two-Step Approach for Classification in Alzheimer's Disease. Sensors 22(11): 3966 (2022) - [j27]Laura Verde, Nadia Brancati, Giuseppe De Pietro, Maria Frucci, Giovanna Sannino
A Deep Learning Approach for Voice Disorder Detection for Smart Connected Living Environments. ACM Trans. Internet Techn. 22(1): 8:1-8:16 (2022) - 2021
- [j26]Laura Verde
Exploring the Use of Artificial Intelligence Techniques to Detect the Presence of Coronavirus Covid-19 Through Speech and Voice Analysis. IEEE Access 9: 65750-65757 (2021) - [j25]Antonio Celesti
Artificial Intelligence for Health. Comput. 10(8): 100 (2021) - [j24]Khan Muhammad
Human action recognition using attention based LSTM network with dilated CNN features. Future Gener. Comput. Syst. 125: 820-830 (2021) - [j23]Antonio Celesti
Guest Editorial Enabling Technologies for Next Generation Telehealthcare. IEEE J. Biomed. Health Informatics 25(12): 4240-4242 (2021) - [c37]Giovanna Sannino, Giuseppe De Pietro, Ivanoe De Falco:
Automatic Extraction of Interpretable Knowledge to Predict the Survival of Patients with Heart Failure. CHASE 2021: 166-173 - 2020
- [j22]Victor Hugo C. de Albuquerque, Deepak Gupta
Special issue on Bio-inspired optimization techniques for Biomedical Data Analysis: Methods and applications. Appl. Soft Comput. 95: 106672 (2020) - [j21]Khan Muhammad
Cost-Effective Video Summarization Using Deep CNN With Hierarchical Weighted Fusion for IoT Surveillance Networks. IEEE Internet Things J. 7(5): 4455-4463 (2020) - [j20]Giovanna Sannino
Non-Invasive Risk Stratification of Hypertension: A Systematic Comparison of Machine Learning Algorithms. J. Sens. Actuator Networks 9(3): 34 (2020) - [c36]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Photoplethysmography and Machine Learning for the Hypertension Risk Stratification. GLOBECOM (Workshops) 2020: 1-6 - [p1]Giovanna Sannino, Giuseppe De Pietro, Laura Verde
Healthcare Systems: An Overview of the Most Important Aspects of Current and Future m-Health Applications. Connected Health in Smart Cities 2020: 213-231
2010 – 2019
- 2019
- [j19]Laura Verde
Dysphonia Detection Index (DDI): A New Multi-Parametric Marker to Evaluate Voice Quality. IEEE Access 7: 55689-55697 (2019) - [j18]Laura Verde
Leveraging Artificial Intelligence to Improve Voice Disorder Identification Through the Use of a Reliable Mobile App. IEEE Access 7: 124048-124054 (2019) - [j17]Ivanoe De Falco, Giuseppe De Pietro, Antonio Della Cioppa
Evolution-based configuration optimization of a Deep Neural Network for the classification of Obstructive Sleep Apnea episodes. Future Gener. Comput. Syst. 98: 377-391 (2019) - [j16]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Towards a cyber physical system for personalised and automatic OSA treatment. IET Cyper-Phys. Syst.: Theory & Appl. 4(2): 156-163 (2019) - [j15]Antonio Celesti, Antoine B. Bagula, Ivanoe De Falco, Pedro Brandão
Emerging Networked Computer Applications for Telemedicine. J. Netw. Comput. Appl. 130: 104-106 (2019) - [j14]Giovanna Sannino
Artificial Intelligence for Mobile Health Data Analysis and Processing. Mob. Inf. Syst. 2019: 2673463:1-2673463:2 (2019) - [j13]Giovanna Sannino
A Continuous Noninvasive Arterial Pressure (CNAP) Approach for Health 4.0 Systems. IEEE Trans. Ind. Informatics 15(1): 498-506 (2019) - 2018
- [j12]Laura Verde
Voice Disorder Identification by Using Machine Learning Techniques. IEEE Access 6: 16246-16255 (2018) - [j11]Laura Verde
A methodology for voice classification based on the personalized fundamental frequency estimation. Biomed. Signal Process. Control. 42: 134-144 (2018) - [j10]Ugo Cesari, Giuseppe De Pietro
A new database of healthy and pathological voices. Comput. Electr. Eng. 68: 310-321 (2018) - [j9]Giovanna Sannino, Giuseppe De Pietro
A deep learning approach for ECG-based heartbeat classification for arrhythmia detection. Future Gener. Comput. Syst. 86: 446-455 (2018) - [c35]Ivanoe De Falco, Giuseppe De Pietro, Antonio Della Cioppa, Giovanna Sannino, Umberto Scafuri, Ernesto Tarantino:
Preliminary Steps towards Efficient Classification in Large Medical Datasets: Structure Optimization for Deep Learning Networks through Parallelized Differential Evolution. HEALTHINF 2018: 633-640 - [c34]Ivanoe De Falco, Giuseppe De Pietro, Giovanna Sannino, Umberto Scafuri, Ernesto Tarantino, Antonio Della Cioppa, Giuseppe A. Trunfio
Deep Neural Network Hyper-Parameter Setting for Classification of Obstructive Sleep Apnea Episodes. ISCC 2018: 1187-1192 - 2017
- [j8]Giovanna Sannino
A Wellness Mobile Application for Smart Health: Pilot Study Design and Results. Sensors 17(3): 611 (2017) - [c33]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
A Statistical Analysis for the Evaluation of the Use of Wearable and Wireless Sensors for Fall Risk Reduction. HEALTHINF 2017: 508-516 - [c32]Salvatore Naddeo, Laura Verde, Manolo Forastiere, Giuseppe De Pietro, Giovanna Sannino:
A Real-time m-Health Monitoring System: An Integrated Solution Combining the Use of Several Wearable Sensors and Mobile Devices. HEALTHINF 2017: 545-552 - [c31]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Detection of falling events through windowing and automatic extraction of sets of rules: Preliminary results. ICNSC 2017: 661-666 - [c30]Giuseppe Caggianese
A Rehabilitation System for Post-operative Heart Surgery. IIMSS 2017: 554-564 - [c29]Seyed Amin Pouriyeh, Sara Vahid, Giovanna Sannino, Giuseppe De Pietro, Hamid R. Arabnia
A comprehensive investigation and comparison of Machine Learning Techniques in the domain of heart disease. ISCC 2017: 204-207 - [c28]Giuseppe Caggianese
Cardiac Surgery Rehabilitation System (CSRS) for a Personalized Support to Patients. SITIS 2017: 83-90 - 2016
- [j7]Salvatore Cuomo
A revised scheme for real time ECG Signal denoising based on recursive filtering. Biomed. Signal Process. Control. 27: 134-144 (2016) - [c27]Giovanna Sannino, Alessio Graziani, Giuseppe De Pietro, Roberto Pratola
Wellness & LifeStyle Server: a Platform for Anthropometric and LifeStyle Data Analysis. 3PGCIC 2016: 337-347 - [c26]Laura Verde, Giuseppe De Pietro, Giovanna Sannino:
An Easy Approach for the Classification of Children's Voices based on the Fundamental Frequency Estimation. HEALTHINF 2016: 570-577 - [c25]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Easy fall risk assessment by estimating the Mini-BES test score. HealthCom 2016: 1-5 - [c24]Julio Cesar Bellido, Giuseppe De Pietro, Giovanna Sannino:
A Control Cycle for the Automatic Assisted Positioning of Auscultation Sensors. ICT4AgeingWell 2016: 53-60 - [c23]Laura Verde
Vox4Health: Preliminary Results of a Pilot Study for the Evaluation of a Mobile Voice Screening Application. ISAmI 2016: 131-140 - [c22]Antonio Celesti
New trends in Biotechnology: The point on NGS Cloud computing solutions. ISCC 2016: 267-270 - 2015
- [j6]Giovanna Sannino, Ivanoe De Falco
A supervised approach to automatically extract a set of rules to support fall detection in an mHealth system. Appl. Soft Comput. 34: 205-216 (2015) - [j5]Giovanna Sannino, Paolo Melillo, Saverio Stranges
Blood Pressure Drop Prediction by using HRV Measurements in Orthostatic Hypotension. J. Medical Syst. 39(11): 143:1-143:7 (2015) - [j4]Giovanna Sannino, Paolo Melillo, Saverio Stranges
Short term Heart Rate Variability to predict blood pressure drops due to standing: a pilot study. BMC Medical Informatics Decis. Mak. 15-S(3): S2 (2015) - [c21]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Indirect Blood Pressure Evaluation by Means of Genetic Programming. BIOSTEC (Selected Papers) 2015: 75-92 - [c20]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Non-Invasive Estimation of Blood Pressure through Genetic Programming - Preliminary Results. BIODEVICES 2015: 241-249 - [c19]Paolo Melillo, Rossana Castaldo
Wearable technology and ECG processing for fall risk assessment, prevention and detection. EMBC 2015: 7740-7743 - [c18]Salvatore Cuomo
A Novel O(n) Numerical Scheme for ECG Signal Denoising. ICCS 2015: 775-784 - [c17]Laura Verde
An m-health system for the estimation of voice disorders. ICME Workshops 2015: 1-6 - [c16]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
Genetic Programming for a Wearable Approach to Estimate Blood Pressure Embedded in a Mobile-Based Health System. ICTAI 2015: 775-783 - [c15]Giovanna Sannino, Ivanoe De Falco, Giuseppe De Pietro:
On Evaluating Blood Pressure Through Photoplethysmography. IoT 360 (1) 2015: 523-529 - [c14]Ivanoe De Falco, Giuseppe De Pietro, Giovanna Sannino:
On Finding Explicit Rules for Personalized Forecasting of Obstructive Sleep Apnea Episodes. IRI 2015: 326-333 - [c13]Laura Verde
A noise-aware methodology for a Mobile Voice Screening application. IWASI 2015: 193-198 - [c12]Julio Cesar Bellido, Giuseppe De Pietro, Giovanna Sannino:
A prototype of a real-time solution on mobile devices for heart tele-auscultation. PETRA 2015: 30:1-30:8 - [c11]Salvatore Cuomo
A framework for ECG denoising for mobile devices. PETRA 2015: 48:1-48:4 - 2014
- [j3]Giovanna Sannino
A mobile system for real-time context-aware monitoring of patients' health and fainting. Int. J. Data Min. Bioinform. 10(4): 407-423 (2014) - [j2]Giovanna Sannino
Monitoring Obstructive Sleep Apnea by means of a real-time mobile system based on the automatic extraction of sets of rules through Differential Evolution. J. Biomed. Informatics 49: 84-100 (2014) - [j1]Giovanna Sannino
An Automatic Rules Extraction Approach to Support OSA Events Detection in an mHealth System. IEEE J. Biomed. Health Informatics 18(5): 1518-1524 (2014) - [c10]Giovanna Sannino
Multi-purpose mobile monitoring system based on automatic extraction of rule-sets. BHI 2014: 630-634 - [c9]Giovanna Sannino
A General-Purpose mHealth System Relying on Knowledge Acquisition through Artificial Intelligence. ISAmI 2014: 107-115 - [c8]Giovanna Sannino, Paolo Melillo, Giuseppe De Pietro, Saverio Stranges, Leandro Pecchia:
To What Extent It Is Possible to Predict Falls due to Standing Hypotension by Using HRV and Wearable Devices? Study Design and Preliminary Results from a Proof-of-Concept Study. IWAAL 2014: 167-170 - 2013
- [c7]Giovanna Sannino
Automatic Extraction of an Effective Rule Set for Fall Detection for a Real-Time Mobile Monitoring System. DeSE 2013: 87-92 - [c6]Giovanna Sannino
Detecting Obstructive Sleep Apnea events in a real-time mobile monitoring system through automatically extracted sets of rules. Healthcom 2013: 16-20 - [c5]Giovanna Sannino
Automatic extraction of effective rule sets for Obstructive Sleep Apnea detection for a real-time mobile monitoring system. IRI 2013: 247-253 - 2012
- [c4]Giovanna Sannino
A U-HealthCare System for Home Monitoring. ISAmI 2012: 197-200 - 2011
- [c3]Giovanna Sannino
A smart context-aware mobile monitoring system for heart patients. BIBM Workshops 2011: 655-695 - [c2]Giovanna Sannino
An Evolved eHealth Monitoring System for a Nuclear Medicine Department. DeSE 2011: 3-6 - 2010
- [c1]Antonio Coronato
Middleware Services for Pervasive Monitoring Elderly and Ill People in Smart Environments. ITNG 2010: 810-815
Coauthor Index
[j33] [j30] [j28] [j27] [j26] [c37] [j20] [c36] [p1] [j19] [j18] [j17] [j16] [j14] [j13] [j12] [j11] [j10] [j9] [c35] [c34] [j8] [c33] [c32] [c31] [c30] [c29] [j7] [c27] [c26] [c25] [c24] [c23] [j6] [j5] [j4] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [j3] [j2] [j1] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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last updated on 2025-03-10 20:47 CET by the dblp team
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