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Cross-domain Super-Resolution in Medical Imaging
Vincenzo Bevilacqua;Antonio Di Marino;Emanuel Di Nardo;Angelo Ciaramella;Ivanoe De Falco;Giovanna Sannino
2024 IEEE Symposium on Computers and Communications (ISCC)
Year: 2024 | Conference Paper |
The use of Super-Resolution SR algorithms applied to Magnetic Resonance Images (MRIs) is increasingly common in the medical field. Increasing the resolution of images allows physicians to more easily observe image details. Over the years, several SR approaches have been tried by researchers. Among the various approaches, Diffusion Models (DMs) have been shown to perform well in the SR task. In thi...Show More
Stress Detection Using Multimodal Physiological Signals With Machine Learning From Wearable Devices
Pranita Subhash Shedage;Seyedamin Pouriyeh;Reza M. Parizi;Meng Han;Giovanna Sannino;Nasrin Dehbozorgi
2024 IEEE Symposium on Computers and Communications (ISCC)
Year: 2024 | Conference Paper |
Stress is considered one of the most prevalent concerns among individuals. Studies have shown that experiencing long-term stress can cause severe health issues such as cardiovascular diseases, hypertension, depression, etc. Preventative measures, such as early stress detection, can help individuals mitigate these health issues. When a person gets stressed, physiological values like blood volume pu...Show More
Bridging Clinical Gaps: Multi-Dataset Integration for Reliable Multi-Class Lung Disease Classification with DeepCRINet and Occlusion Sensitivity
2024 IEEE Symposium on Computers and Communications (ISCC)
Year: 2024 | Conference Paper |
This research presents DeepCRINet, a deep learning (DL) model designed for reliable performance across various Chest Radiography Images (CRIs) datasets, in response to the urgent need for quick and accurate lung disease identification utilizing CRIs. Our method builds on earlier research, which frequently used single-source datasets that might not adequately represent the heterogeneity present in ...Show More
The Tele-Rehabilitaion as a Service (TRaaS) Project: Rationale, Study Design, and Methodology
Antonio Celesti;Giovanna Sannino;Mario Bochicchio;Maria Fazio;Massimo Villari;Fabrizio Celesti;Mirjam Bonanno;Rocco Salvatore Calabrò
2023 IEEE 19th International Conference on e-Science (e-Science)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Tele-rehabilitation has recently emerged as an effective solution for providing assisted living, increasing clinical outcomes, positively enhancing patients' Quality of Life (QoL) and fostering their reintegration into society, also pushing down clinical costs. Cloud computing in combination with Edge Computing, the Internet of Things (IoT), Big Data storage and analytics, and Artificial Intellige...Show More
A Novel Deep Learning Approach for Colon and Lung Cancer Classification Using Histopathological Images
2023 IEEE 19th International Conference on e-Science (e-Science)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
Colon and Lung cancers are two of the most common causes of mortality in adults. They may simultaneously form in organs and have a detrimental effect on human life. There is a high risk that cancer will spread to the two organs if it is not discovered in the early stages. One of the most essential elements of successful therapy is the histological diagnosis of such cancers. Deep learning algorithm...Show More
Automatic Extraction of Interpretable Knowledge to Predict the Survival of Patients with Heart Failure
2021 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)
Year: 2021 | Conference Paper |
Cited by: Papers (1)
Cardiovascular diseases cause the death of almost 18 million people each year. Heart failure takes place when the heart does not pump a sufficient amount of blood to the body and is one of the most common causes of death. Healthcare technologies and Artificial Intelligence algorithms constitute promising solutions useful not only for the monitoring of people's health but also in order to tell whic...Show More
Exploring the Use of Artificial Intelligence Techniques to Detect the Presence of Coronavirus Covid-19 Through Speech and Voice Analysis
Laura Verde;Giuseppe De Pietro;Ahmed Ghoneim;Mubarak Alrashoud;Khaled N. Al-Mutib;Giovanna Sannino
The Covid-19 pandemic represents one of the greatest global health emergencies of the last few decades with indelible consequences for all societies throughout the world. The cost in terms of human lives lost is devastating on account of the high contagiousness and mortality rate of the virus. Millions of people have been infected, frequently requiring continuous assistance and monitoring. Smart h...Show More
Blood pressure is a basic physiological parameter in the cardiovascular circulatory system. PhotoPlethysmoGraphy (PPG) signal represents a convenient, wearable, and low-cost technology that can be applied to various aspects of cardiovascular monitoring, including the detection of blood pressure, i.e., the hypertension level. The goal of this paper is to explore the behavior of a set of machine lea...Show More
Cost-Effective Video Summarization Using Deep CNN With Hierarchical Weighted Fusion for IoT Surveillance Networks
Khan Muhammad;Tanveer Hussain;Muhammad Tanveer;Giovanna Sannino;Victor Hugo C. de Albuquerque
IEEE Internet of Things Journal
Cited by: Papers (79)
Video summarization (VS) has attracted intense attention recently due to its enormous applications in various computer vision domains, such as video retrieval, indexing, and browsing. Traditional VS researches mostly target at the effectiveness of the VS algorithms by introducing the high quality of features and clusters for selecting representative visual elements. Due to the increased density of...Show More
Leveraging Artificial Intelligence to Improve Voice Disorder Identification Through the Use of a Reliable Mobile App
Laura Verde;Giuseppe De Pietro;Mubarak Alrashoud;Ahmed Ghoneim;Khaled N. Al-Mutib;Giovanna Sannino
The evolution of the Internet of Things, cloud computing and wireless communication has contributed to an advance in the interconnectivity, efficiency and data accessibility in smart cities, improving environmental sustainability, quality of life and well-being, knowledge and intellectual capital. In this scenario, the satisfaction of security and privacy requirements to preserve data integrity, c...Show More
Dysphonia Detection Index (DDI): A New Multi-Parametric Marker to Evaluate Voice Quality
Laura Verde;Giuseppe De Pietro;Mubarak Alrashoud;Ahmed Ghoneim;Khaled N. Al-Mutib;Giovanna Sannino
The rapid diffusion of voice disorders and the lack of appropriate knowledge about the problem have prompted the search for novel and reliable approaches to detect dysphonia, through easy and accessible instruments such as mobile devices. These systems represent, in fact, valid instruments to improve the patient care not only to facilitate the monitoring of symptoms of any diseases but also suppor...Show More
A Continuous Noninvasive Arterial Pressure (CNAP) Approach for Health 4.0 Systems
Health 4.0 can provide effective ways to improve the health status of subjects by taking advantage of cyber-physical systems and Internet of things technologies for the solution of healthcare problems. One of these is represented by suitably estimating blood pressure values of subjects in a continuous, real-time, and noninvasive way. To address it, we propose an approach only requiring a photoplet...Show More
Deep Neural Network Hyper-Parameter Setting for Classification of Obstructive Sleep Apnea Episodes
Ivanoe De Falco;Giuseppe De Pietro;Giovanna Sannino;Umberto Scafuri;Ernesto Tarantino;Antonio Della Cioppa;Giuseppe A. Trunfio
2018 IEEE Symposium on Computers and Communications (ISCC)
Year: 2018 | Conference Paper |
Cited by: Papers (14)
The wide availability of sensing devices in the medical domain causes the creation of large and very large data sets. Hence, tasks as the classification in such data sets becomes more and more difficult. Deep Neural Networks (DNNs) are very effective in classification, yet finding the best values for their hyper-parameters is a difficult and time-consuming task. This paper introduces an approach t...Show More
Nowadays, the use of mobile devices in the healthcare sector is increasing significantly. Mobile technologies offer not only forms of communication for multimedia content (e.g. clinical audio-visual notes and medical records) but also promising solutions for people who desire the detection, monitoring, and treatment of their health conditions anywhere and at any time. Mobile health systems can con...Show More
Cardiac Surgery Rehabilitation System (CSRS) for a Personalized Support to Patients
Giuseppe Caggianese;Mariaconsiglia Calabrese;Luigi Gallo;Giovanna Sannino;Carmine Vecchione
2017 13th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)
Year: 2017 | Conference Paper |
Cited by: Papers (1)
For a successful rehabilitation after cardiac surgery, it is crucial to have a carefully personalized, structured, and supervised physiotherapy program. Due to erroneous or unsupervised physiotherapy, nearly 50% of surgeries fail. Researchers have tried to leverage advances in wearable sensors and motion tracking to build affordable, automated, and customizable rehabilitation systems that help bot...Show More
A comprehensive investigation and comparison of Machine Learning Techniques in the domain of heart disease
Seyedamin Pouriyeh;Sara Vahid;Giovanna Sannino;Giuseppe De Pietro;Hamid Arabnia;Juan Gutierrez
2017 IEEE Symposium on Computers and Communications (ISCC)
Year: 2017 | Conference Paper |
Cited by: Papers (166)
This paper aims to investigate and compare the accuracy of different data mining classification schemes, employing Ensemble Machine Learning Techniques, for the prediction of heart disease. The Cleveland data set for heart diseases, containing 303 instances, has been used as the main database for the training and testing of the developed system. 10-Fold Cross-Validation has been applied in order t...Show More
Detection of falling events through windowing and automatic extraction of sets of rules: Preliminary results
2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)
Year: 2017 | Conference Paper |
Cited by: Papers (4)
Fall detection is very important for the health care especially for elderly people. The automatic discovery of falls in real time with the ability to differentiate them from normal daily activities is crucial. To achieve this aim, this paper proposes an approach based on getting data through a tag placed on the subject's chest, a windowing of the data, the automatic extraction through the DEREx to...Show More
Easy fall risk assessment by estimating the Mini-BES test score
2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)
Year: 2016 | Conference Paper |
Cited by: Papers (1)
The aim of this study is to identify an explicit relationship between life-style and the risk of falling under the form of a mathematical model. Starting from some personal and behavioral information as, e.g., weight, height, age, data about physical activity habits, and concern about falling, the model would easily estimate the score of the Mini-Balance Evaluation Systems (Mini-BES) test. This wo...Show More
New trends in Biotechnology: The point on NGS Cloud computing solutions
Antonio Celesti;Maria Fazio;Fabrizio Celesti;Giovanna Sannino;Salvatore Campo;Massimo Villari
2016 IEEE Symposium on Computers and Communication (ISCC)
Year: 2016 | Conference Paper |
Cited by: Papers (9)
The advent of Cloud computing is changing the way of conceiving information and communication systems in different application fields including Biotechnology. In this context, an emerging research field is Next-Generation Sequencing (NGS) that includes several recent technologies allowing sequencing DNA and that have revolutionized the study of genomics and molecular biology. These cutting-edge se...Show More
Genetic Programming for a Wearable Approach to Estimate Blood Pressure Embedded in a Mobile-Based Health System
2015 IEEE 27th International Conference on Tools with Artificial Intelligence (ICTAI)
Year: 2015 | Conference Paper |
Continuous blood pressure (BP) measurement is an important issue in the medical field. The hypothesis of existence of a nonlinear relationship between plethysmography (PPG) and BP values has been investigated in this paper. If this hypothesis is true, then it is possible to indirectly measure patient's BP in a non-invasive way through the application of a wearable wireless PPG sensor to patient's ...Show More
Wearable technology and ECG processing for fall risk assessment, prevention and detection
Paolo Melillo;Rossana Castaldo;Giovanna Sannino;Ada Orrico;Giuseppe de Pietro;Leandro Pecchia
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2015 | Conference Paper |
Cited by: Papers (31)
Falls represent one of the most common causes of injury-related morbidity and mortality in later life. Subjects with cardiovascular disorders (e.g., related to autonomic dysfunctions and postural hypotension) are at higher risk of falling. Autonomic dysfunctions increasing the risk of falling in the short and mid-term could be assessed by Heart Rate Variability (HRV) extracted by electrocardiograp...Show More
On Finding Explicit Rules for Personalized Forecasting of Obstructive Sleep Apnea Episodes
2015 IEEE International Conference on Information Reuse and Integration
Year: 2015 | Conference Paper |
Cited by: Papers (7)
Obstructive Sleep Apnea (OSA) is a breathing disorder that takes place during sleep, and has both short -- as well as long -- term consequences on patient's health. Real -- time monitoring for a patient can be carried out by making use of ElectroCardioGraphy (ECG) recordings. This paper introduces a methodology to forecast OSA events in the minutes following the current time instant. This is accom...Show More
A noise-aware methodology for a Mobile Voice Screening application
Laura Verde;Giuseppe De Pietro;Pierangelo Veltri;Giovanna Sannino
2015 6th International Workshop on Advances in Sensors and Interfaces (IWASI)
Year: 2015 | Conference Paper |
Cited by: Papers (2)
Dysphonia is a qualitative and quantitative alteration of the voice due to a structural or functional modification of one or more organs involved in voice production. Voice disorders are prevalent in certain working categories, particularly those of teachers, singers and actors. It is possible to evaluate the state of health of a voice through the acoustic analysis of the speech signal. This provi...Show More
An m-health system for the estimation of voice disorders
Laura Verde;Giuseppe De Pietro;Pierangelo Veltri;Giovanna Sannino
2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)
Year: 2015 | Conference Paper |
Cited by: Papers (12)
In recent years, the prevalence of voice disorders has been increasing dramatically, mainly due to unhealthy lifestyles and voice abuse. An impairment in the ability to produce the sound of the voice is indicated by the medical term Dysphonia. This disorder impacts on the quality of life of the population in general, but especially of professional voice users, like teachers or singers, for whom dy...Show More
Multi-purpose mobile monitoring system based on automatic extraction of rule-sets
IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
Year: 2014 | Conference Paper |
Real-time tele-monitoring technology is very useful for remotely monitoring patients' vital parameters and for ensuring mobility of both patient and doctor. In this paper a multi-purpose and multi-parametric tele-monitoring system is described. This system is based on the offline automatic extraction of knowledge from databases expressed as a set of IF...THEN rules that are used by a rule-based mo...Show More
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