Department of Computer Science
University of Cyprus

x ehealth logoProgramme: Horizon 2020 - Research and Innovation Framework Programme

C. S. Pattichis (PI)

Sep. 2020 – Aug. 2022

Proposal Acronym: X-eHealth

Proposal Title:  X-eHealthExchanging Electronic Health Records in a common framework

Proposal Budget: €63,375

Website: http://www.x-ehealth.eu/

 

Description:

X-eHealth stands herein for a project of strategic relevance for tomorrow’s European eHealth Union. Assembling a shared commitment of 47 health actors, the underlying idea of this project is to develop the basis for a workable, interoperable, secure and cross border Electronic Health Record exchange Format in order to lay the foundation for the advance of eHealth sector while using the 3 pillars put forward by the EC as reference. 

Aimed at promoting a faster and sustainable EU digital transformation, this Cooperative and Support Action is made up of 8 Work Package in which 4 exclusively focus on technical-functional activities (WP4 to WP7). From Generic Aspects to System Architecture and Integration, passing by Functional and Technical Specifications, X-eHealth objective is to move towards a uniform interoperable data-sharing format framework. In addition, to enhance EU’s public health state of play, WP1 and WP8 are responsible for implementation studies, practicality and continuity of eHealth interoperability development.

 

 

caip logoThe 19th International Conference on Computer Analysis of Images and Patterns (CAIP) will be held between 27 September – 01 October 2021.

Due to the COVID-19 global pandemic, CAIP 2021 will be held as a virtual conference. The Organizing Committee would like to thank you for your commitment and support and reassure you that they are dedicated to offering the best possible online experience to attendees.

Extended Paper Submission Deadline - 05 May 2021

 

Important Dates:

Special Sessions proposal submission
05 May 2021

Special Sessions acceptance notification
10 May 2021

Paper Submission
05 May 2021

 

Author notification
15 June 2021

Camera-ready paper due
01 July 2021

 

Early bird registration
31 July 2021

 

For more information about CAIP 2021, please click here.

IEEE EBMS Grand Challenges Forum

Data science is an emerging discipline that will be instrumental in accelerating healthcare innovation and transforming the healthcare industry to improve the quality and cost of services provided to patients. Data science, broadly defined, includes the tools, techniques, and theoretical underpinnings for enabling machine learning and artificial intelligence (AI) to be applied to large, diverse, complex, longitudinal, and distributed data sets in order to extract useful information and knowledge. Machine learning and AI have already led to significant successes in many health-related fields including medical image classification, segmentation, prediction, and decision making. The field of data science promises to accelerate the applications and successes, specifically by enabling the scaling to “big” and heterogeneous data.
 
To address the research and translational advances and challenges in healthcare-focused data science, the IEEE EMBS Grand Challenge Forum on Data Science and Engineering in Healthcare will be held on Feb 10-13, 2021. The forum aims to highlight and discuss the challenges and opportunities of Data Science innovations in healthcare, medicine and biology, and how these innovations can be translated into cutting-edge healthcare and biomedical engineering curriculums.
 
The forum will have the following four symposiums:
 
  1. Grand Challenges in Data Science and Engineering in Healthcare: Medical Imaging
  2. Grand Challenges in Data Science and Engineering in Healthcare: Precision Medicine
  3. Grand Challenges in Data Science and Engineering in Healthcare: Digital Healthcare
  4. Grand Challenges in Data Science and Engineering in Healthcare: Brain and Neural Systems

You can find the full Symposium's program here.

We believe that the IEEE EMBS Forum will provide a unique platform for scientists, engineers, and students to focus on translational data science and engineering research and healthcare innovations, as well as the need for a paradigm shift in engineering and science education and their impact on healthcare and economic growth.
 
Due to the long-term impact of the COVID-19 pandemic, the organizing committee has decided to offer the Forum in a virtual format only to ensure a safe environment and to make participation possible for more people. We hope you would join us. 
 
Please note registration is free and required to attend the IEEE EMBS Grand Challenges Forum on Data Science: https://grand-challenges.embs.org/2021datascience/

 

CWSPIYOU ARE ALL WELCOME
 
13th Cyprus Workshop on Signal Processing and Informatics (CWSPI)
September 21st, 2020, 18:45-22:00 hrs

via Google Meet at the following link: https://meet.google.com/ger-mtbz-xrr

The final program of the 13th Cyprus Workhshop on Signal Processing and Informatics - can be downloaded from here.
 
 

Technical Program

 

TIME

SESSIONS

18:45

Introductions

18:55-19:00

Welcome

Andreas Spanias

Arizona State University, USA

 

SESSION 1: IoT and Sensing

Andreas Spanias

Arizona State University, USA

19:00-19:10

Energy Efcient Reuse of Mobile Nodes for Congestion Control in Wireless Sensor Networks

Natalie Temene, Charalampos Sergiou, chryssis Georgiou, Vasos Vasiliou

Department of Computer Science, University of Cyprus, Nicosia, Cyprus

19:10-19:20

Sensor Synchronization for Android Spatial Applications

Andreas Spanias1

1Maria Christofi, 2,3George Plastiras, 2,3Rafaella Elia, 2Vaggelis Tsiourtis, 2,3Theocharis Theocharides, 1Miltiadis Katsaros

1National Technical University of Athens, Athens, Greece

2University of Cyprus, Nicosia, Cyprus

3KIOS Research and Innovation Centre of Excellence, Nicosia, Cyprus

19:20-19:30

The Navarchos Fleet Management Platform

I.Constantinou1, C. Constantinou1, P. Gouvas2, T. Bouras2

1Istognosis Ltd Cyprus, 2UBITECH Limited Cyprus

 

SESSION 2: Machine Learning and Signal Processing

Chair: Marios Neofytou

3AeHealth LTD

19:30-19:40

Machine Learning based MEMS Sensor Calibration

Gowtham Muniraju, Andreas Spanias,

SenSIP Center, ECEE, ASU

19:40-19:50

Unsupervised Audio Source Separation using Generative Priors

Vivek Narayanaswamy1, Jayaraman, Thiagarajan2, Rushil Anirudh2, Andreas Spanias1

1SenSIP Center, ASU, 2Lawrence Livermore National Labs

19:50-20:00

Graph Representation Learning using Deep Neural Networks

Uday Shankar1, Jayaraman Thiagarajan2, Andreas Spanias1

1SenSIP Center, ASU, 2Lawrence Livermore National Labs

 

SESSION 3: Computer Vision

Chair: Andreas Panayides

University of Cyprus

20:00-20:10

Cognitive Swarm of UAVs for Search and Rescue

Guillaume Voirin, Loizos Michael

Open University of Cyprus & Research Center on Interactive Media, Smart Systems, and Emerging Technologies

20:10-20:20

Detecting Obstacles for Pedestrians’ Safety

Marios Thoma1, Zenonas Theodosiou1, Harris Partaourides1, Charalambos Tylliros1, Demetris Antoniades1, Andreas Lanitis1,2

1RISE, Nicosia, Cyprus, 2Cyprus University of Technology, Limassol, Cyprus

20:20-20:30

Machine Learning Methods for PV Array Soilage Detection on the Cyprus Solar Dataset

Kristen Jaskie1 and Joshua Martin1, Yiannis Tofis2 Andreas Spanias1

1SenSIP Center, ECEE, ASU, 2KIOS Center, University of Cyprus

20:30-20:40

Cloud Segmentation and Movement Prediction

Sameeksha Katoch, Pavan Turaga, Cihan Tepedelenlioglu, Andreas Spanias

SenSIP Center, ECEE, ASU

 

SESSION 4: Medical Imaging

Chair: Efthyvoulos Kyriacou

Frederick University

20:40-20:50

Detection of Breast Cancer with Mammography: Use of temporal subtraction of sequential mammograms

Kosmia Loizidou, Galateia Skouroumouni, Christos Nikolaou and Costas Pitris

KIOS, University of Cyprus

20:50-21:00

Machine Learning Techniques Comparison for Classification of Barret’s and Dysplasia from In Vivo Esophagus Optical Coherence Tomography Images

Christos Photiou1, George Plastiras1, Guillermo Tearney2, Costas Pitris1

1KIOS Center of Excellence for Intelligent System and Networks, Dept. of Electrical and Computer Engineering, University of Cyprus,

2Massachusetts General Hospital and Harvard medical school 55 Fruit Street, Boston, USA

 

SESSION 5: PhD Presentations – 5 min. (2 to 3 slides)

Costas Pitris

University of Cyprus

21:00-21:05

Extracting Explainable Assessments of Alzheimer’s disease via Machine Learning on brain MRI imaging data

Kleo Achilleos, Nicoletta Prentza, Antonis C. Kakas, Constantinos S. Pattichis

Department of Computer Science, University of Cyprus, Nicosia, Cyprus

21:05-21:10

Argumentation-based framework for Explainable Machine Learning (ARGEML)

Nicoletta Prentzas, Antonis Kakas, Constantinos S. Pattichis

Department of Computer Science, University of Cyprus

21:10-21:15

A Review of Brain MRI Multiple Sclerosis Disease Image Analysis Studies

Andria Nicolaou, Department of Computer Science, University of Cyprus, Nicosia, Cyprus

21:15-21:20

Intelligent Virtual Reality Systems for pain management in cancer patients

Melpo Pittara

Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligent, University of Groningen, Department of Computer Science, University of Cyprus

 

SESSION 6: Elevator Speech Presentations – 2 min (1 to 2 slides)

Constantinos S. Pattichis

University of Cyprus

21:20-21:23

AI for Power Converters

Mohit Malu, Andreas Spanias and Gautam Dasarathy

ECEE, SenSIP, ASU

21:23-21:26

RET Project: Solar Fault Detection and Classification using Machine Learning

Milton Johnson

Bioscience High School, Phoenix

Advisors: Kristen Jaskie and Andreas Spanias,  ECEE, SenSIP, ASU

21:26-21:29

Fault Classification in PV Arrays using Pruned Neural Networks

Sunil Rao, Cihan Tepedelenlioglu and Andreas Spanias

SenSIP, ECEE, ASU

21:29-21:32

Using Machine Learning and Audio Spectral Features For COVID-19 Testing

Michael Esposito

Advisors: Sunil Rao, Vivek Narayanaswami and Andreas Spanias

ECEE, SenSIP, ASU

21:32-21:35

Semi-Supervised Classification via Graph Filtering

Jie Fan, Cihan Tepedelenlioglu and Andreas Spanias

SenSIP Center, ECEE, ASU

21:35-21:38

Space-Based Computational Imaging Systems

Drika Iqbal, Suren Jayasuriya, Andreas Spanias

ASU ECEE, SenSIP

21:38-22:00

CLOSING REMARKS

frontiers vector logoThe COVID-19 pandemic marks one of the greatest global challenges experienced this century. It has led to more than 20 million reported infections and caused more than 800 000 deaths world-wide. Despite attempts at lifting restrictions for lock-downs and seeking ways “back” to a “new normal”, we are far from a stable transition to a new normal life.

Digital Health solutions have already been used in many ways from tracking and tracing apps to deep learning for analysis of computerized tomography images or audio-based diagnosis and early symptom recognition. However, there are many technologies and innovations that remain unexploited with vast potential in improving the reliability, trustability, usability, and explainability of healthcare services: including the speed and quality of diagnosis, healthcare process and results. In addition, novel technology solutions and innovations to adapt processes and technologies are desperately needed. Further, there is a need for new regulatory pathways and processes for rapid testing, approval and integration of these new technologies into practice.

More information can be found in: https://www.frontiersin.org/research-topics/16023/health-technologies-and-innovations-to-effectively-respond-to-the-covid-19-pandemic

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