Welcome to the 4th IEEE International Conference on ICT Solutions for eHealth

in conjunction with the 29th

IEEE Symposium on Computers and Communications (ISCC)

26 - 29 June, 2024 - Paris, France


Submit your paper now:
https://edas.info/N32201



e-Health is one of the major research topics that have been attracting cross-disciplinary research groups. The deployment of new emerging ICT technologies for Health, especially based on Cloud computing, Internet of Things (IoT), and Computational Intelligence, is attracting the interest of many researchers.

Following five successful workshop editions, three years ago ICTS4eHealth became an International IEEE Conference, and we are now proud to announce the fourth edition of this popular conference dedicated to ICT solutions for e-Health, especially based on Cloud computing, Internet of Things (IoT), and Computational Intelligence.

The conference will bring together researchers from academia, industry, government, and medical centers in order to present the state of the art in the emerging area of the use of cloud systems in connected health infrastructure and applications, and the use of IoT and Computational Intelligence techniques in the area of eHealth.


                       



Steering Committee

Mission

e-Health is one of the major research topics that have been attracting cross-disciplinary research groups. The deployment of new emerging ICT technologies for Health, especially based on Cloud computing, Internet of Things (IoT), and Computational Intelligence, is attracting the interest of many researchers.

The use of Cloud computing, IoT technologies, and methods typical of Soft Computing and Computational Intelligence have been very prominent recently and can be of great help in finding good solutions to many practical healthcare applications.

For instance, health monitoring, health data storage, health data collection, mobile health, pervasive health, healthcare monitoring, telemedicine, context-aware computing, ubiquitous computing, processing health data in the cloud, securing health data in the cloud and Assistive Technology (AT) are areas of interest that are being addressed using cloud computing and IoT techniques. On the other hand, several challenging issues have raised due to the adoption of such emerging technologies. These include the quality of health data, the ability to retrieve information and use it in health context, as for example in tasks related to machine learning, knowledge discovery, decision support, regression, forecasting, optimization, feature selection, and additionally privacy and security issues of health data while being processed in the cloud, availability of health data, models of context and tele-monitoring of contextual applications.

Following five successful workshop editions, three years ago ICTS4eHealth became an International IEEE Conference, and we are now proud to announce the fourth edition of this popular conference dedicated to ICT solutions for e-Health, especially based on Cloud computing, Internet of Things (IoT), and Computational Intelligence.

The conference will bring together researchers from academia, industry, government, and medical centers in order to present the state of the art in the emerging area of the use of cloud systems in connected health infrastructure and applications, and the use of IoT and Computational Intelligence technique in the area of eHealth.

General Chair

 


Technical Program Co-Chairs

Publicity Chair

Annamaria Ficara

University of Messina, Italy

Honorary Chair

Giuseppe De Pietro

Director of ICAR - CNR, Italy

 

Keynote:

TBA

Talk: TBA

Topics:

Conference Topics Include (But Are Not Limited To):

  • Artificial Intelligence for eHealth
  • Cloud computing applications for eHealth
  • Internet of Things (IoT) applications for eHealth
  • Assistive Technology (AT)
  • Networking and Monitoring in Bio-systems
  • Management and Organization of BME Environments
  • Bioinformatics and Computational Biology and Medicine
  • Monitoring of Vital Functions with Sensor and ICT Systems
  • Biosensors and Sensor Networks
  • Advanced Bio-signal Processing
  • Distributed BME Applications
  • Telehealth, Telecare, Telemonitoring, Telediagnostics
  • e-Healthcare, m-Healthcare, x-Health
  • Assisted Living
  • Smartphones in BME Applications
  • Social Networking, Computing and Education for Health
  • Computer Aided Diagnostics
  • Improved Therapeutic and Rehabilitation Methods
  • Intelligent Bio-signal Interpretation
  • Explainable and Interpretable AI models for Health, Biology and Medicine
  • Federated Learning for Medical and Healthcare Data
  • Signal and Image processing for Health
  • Data and Visual Mining for Diagnostics
  • Advanced Medical Visualization Techniques
  • Personalized Medical Devices and Approaches
  • Modelling and Computer Simulations in BME
  • Human Responses in Extreme Environments
  • Other Emerging Topics in BME
  • e-Accessibility, web accessibility
  • Hardware & Software personalized assistive technologies
  • Assistive systems for users who are blind or visually impaired
  • Integration between home-based assistive technologies and patient health data
  • User-centered design of electronic assistive technologies
  • Usability of assistive technologies
  • Computer vision in AT
  • User interfaces for home-based assistive technologies
  • Use of prescription systems and assistive technologies
  • Experience from real world assistive environment deployment
  • Assistive Technologies for Urban Environments
  • Healthcare modeling and simulation
  • Knowledge discovery and decision support
  • Biomedical data processing
  • Wearable devices
  • Sensor-based mHealth applications
  • Security and Privacy in eHealth

The use of Soft Computing/Computational Intelligence methods in facing problems in the above topics is highly welcome, although by no way compulsory.

Submission

ICTS4eHealth main conference:

Manuscripts should describe original work and should be no more than 7 pages in the IEEE double-column proceedings format, including tables, figures and references.

In order to download manuscript templates for IEEE conference proceedings use the following link: https://www.ieee.org/conferences/publishing/templates.html

Papers can be submitted directly to EDAS: https://edas.info/N32201

Note that accepted papers up to 6 pages will be published with no additional charge. Exceeding pages will be charged an additional fee. Papers exceeding 7 pages will not be accepted.

At least one author of each accepted paper is required to register to the conference and present the paper. Only registered and presented papers will be published in the conference proceedings.

Accepted papers will be included in the proceedings of ISCC 2024, of which ICTS4eHealth conference is a co-located event, and will be submitted for inclusion to IEEE Xplore. The ICTSeHealth and ISCC proceedings have been indexed in the past by ISI, DBLP and Scopus.





Call for Special Session Proposals

The Steering Committee of IEEE ICTS4eHealth 2024 invites and welcomes you to submit proposals for exciting Special Sessions which should mandatorily include paper submission on topics relevant to the conference areas.

The Special Session intends to address current and future research and application topics, through experts in the field and may include, other than the paper presentation, discussions, and interactions among participants.

If you intend to propose and organize a special session, please submit a proposal by sending an email to icts4eHealth@icar.cnr.it , using the following template:

  • Title of the Special Session
  • A brief description of the area of concern (approx. 100 words), with special focus on why this is considered to be an interesting and significant topic.
  • The name and contact information of two or more Special Sessions chairs, who are willing to promote and organize a sufficient amount of quality submissions to the Special Sessions. Please also indicate the short bio of the organizers.

Once approved, it is the duty of the organizers to publicize the Special Session among researchers and practitioners in the field and attract a sufficient number of papers. Papers submitted to Special Session will undergo the same review process as regular papers. The Special Session organizers are responsible for managing the review process, assuring at least three reviews per paper. This includes the creation of a Special Session Technical Program Committee.

Before starting the review process, Special Session organizers must explicitly declare papers which present a conflict of interest for them. Any conflict of interest will be managed by the ICTS4eHealth organizers.

A minimum of 8 submitted papers, with an acceptance rate of 50% maximum, is required for each session.

  • Submission deadline for Special Session Proposals: February 26, 2024 - EXPIRED
  • Notification of acceptance: February 29, 2024- EXPIRED


Accepted Special Sessions:

SS-BTIoMTHA: Blockchain Technology and Internet of Medical Things for Healthcare Applications

The utilization of blockchain technology and internet of things has been fascinated among the researchers due to its vast opportunities for harnessing huge amount of data. The promising technological trend enables several advantages across various fields like healthcare, smart farming, manufacturing, Energy Management, Supply Chain Management, Environmental monitoring, Home automation and transportation. IoMT helps the intelligent healthcare systems by providing innovative smart health services to collect sensitive information and transferring and controlling of health care infrastructures, however the current centralized nature of health care system has significant challenges such as data security, privacy, vulnerability, data duplication, fragmented data repositories and communication delays. The integration of blockchain with IoMT has posed the potential for optimizing the smart health care decision making process by analyzing the real time data effectively and also address the above challenges. The communication system leverages for managing different operations of patent’s health condition by monitoring, diagnosing and preventing various diseases. The smart medical devices and implantable devices are used to capture the condition of the patient and transfer the data among health care providers and patients for diagnosing and improving the patient’s health conditions. By fostering the healthcare practitioners to grasp the rationale about AI generated reports and recommendations, the quality of care to advocate the ethical AI deployment. Blockchain and IoMT in smart healthcare systems yields the decentralization in security, computation and storage.

TOPICS (but are not limited to):
  • IoMT-enabled Wearable Devices for Remote Patient Monitoring
  • Real-time Health Monitoring Systems using Trustworthy blockchain
  • Big Data Analytics for Predictive Healthcare Maintenance and blockchain transactions
  • IoMT-enabled Smart Hospitals: Enhancing Patient Care and Operational Efficiency
  • AI integrated blockchain technology for Smart Healthcare Applications
  • IoMT data analytics for Disease Surveillance and Epidemic Prediction
  • Blockchain based IoMT data storage using cryptographic techniques
  • Security and Privacy Challenges in IoT-based Healthcare Systems
  • Secure Blockchain-Enabled Internet of Things: Optimizing Consensus Management
  • Blockchain-enabled Telemedicine and Remote Consultation Services
  • Data Fusion Techniques for Integrating IoT and Blockchain in Healthcare Applications
  • Consensus mechanisms and mining management for Predictive Healthcare Maintenance
  • Integrity and privacy-aware, patient-centric health record access control framework
  • IoT and decentralized mechanism for Disease Surveillance and Epidemic Prediction
  • Protecting healthcare data using blockchain and federated learning techniques
co-Chairs:
  • Dr. Balamurugan Balusamy, Shiv Nadar University, India
  • Dr. M. Lawanyashri, Vellore Institute of Technology, Vellore, India
  • Prof. E. Gangadevi, Loyola College, Chennai, India
  • Dr. K. Santhi, Vellore Institute of Technology, Vellore, India


SS-RAAIMTCNCD: Recent Advancements in the use of Artificial Intelligence for Management and Treatment of Chronic Non Communicable Diseases

Artificial intelligence (AI) is a broad field of computer science focused on creating intelligent machines that can carry out jobs usually done by humans. Due to rapid technological advancements, artificial intelligence (AI) is becoming significantly crucial in different industries, particularly in treatments and healthcare. AI approaches have had a significant impact on addressing health concerns. AI is now being utilised or tested in several healthcare and research applications like as disease detection, chronic condition management, health service delivery, and drug development.
Noncommunicable diseases (NCDs), including heart disease, cancer, chronic respiratory disease, and diabetes, are the primary cause of death globally and pose a growing danger to global health. Non-communicable illness mortality currently surpass the aggregate deaths from all communicable diseases. NCDs cause the death of 41 million individuals annually, or more than 70% of global deaths. Social, economic, and structural changes, such as urbanisation and the prevalence of unhealthy behaviours, have contributed to the NCD problem, resulting in the early deaths of 15 million individuals annually before the age of 70. NCDs are prevalent among working-age individuals, resulting in increased healthcare expenses, reduced work capacity, and financial instability. Combatting non-communicable diseases (NCDs) improves worldwide economic and health stability and aids in achieving the United Nations' Sustainable Development Goals.
In this special session, we will explore into the recent advancements in AI techniques such as, Machine Learning (ML) and Deep Learning (DL) for the management and treatment of chronic non communicable diseases. The purpose of this special session is to provide a forum in which researchers and practitioners explore the various ways AI, ML and DL are changing medical diagnostics and treatment techniques for chronic non communicable diseases.

TOPICS (but are not limited to):
  • AI based diabetes detection
  • AI based hypertension prediction
  • AI based heart attacks detection
  • AI based chronic respiratory illness diagnosis
  • AI based chronic neurological illness detection
  • AI based chronic kidney disease diagnosis
  • AI based cardiovascular diseases diagnosis
  • AI based different types of cancer detection
  • AI based common mental health disorders prediction
  • AI based other non-communicable diseases detection/diagnosis
  • Issues and Challenges in AI based non-communicable disease diagnosis
  • Future research directions in AI based NCDs detection
co-Chairs:
  • Dr. Balasubramaniam S, Digital University Kerala, India
  • Prof. Seifedine Kadry, Noroff University College, Norway


SS-IEMMIDAC: Interpretable and Explainable Models for Medical Image Diagnosis: Advances and Challenges

In the fields of artificial intelligence and healthcare, interpretable and explainable methods for diagnosing medical images are crucial. However, the opacity of some AI models presents challenges in their adoption, particularly in critical domains where interpretability and transparency are paramount. Understanding and interpreting the judgments made by deep learning models—in particular, convolutional neural networks, or CNNs—becomes increasingly critical as these models continue to achieve remarkable performance in the processing of medical images. Healthcare practitioners may learn how CNNs come at diagnoses using interpretable and explainable AI methodologies, which eventually improves trust, transparency, and clinical decision-making. Moreover, this special session aims to explore the latest research, methodologies, and applications focusing on Explainable and Interpretable AI models in health, biology, and medicine. Researchers want to close the knowledge gap between AI-driven forecasts and practical insights by revealing the "black box" of deep learning models, opening the door to more accurate and efficient medical imaging diagnosis. Therefore, the development of interpretable and explainable methods for diagnosing medical images has great potential to enhance patient safety and healthcare results.

TOPICS (but are not limited to):
  • Interpretable models for medical image analysis
  • Explainable AI techniques
  • Visualization methods
  • Novel techniques for explaining AI models in healthcare diagnosis, treatment planning, and prognosis prediction
  • Interpretable machine learning approaches for genomic analysis, personalized medicine, and drug discovery
  • Applications of XAI (Explainable AI) in medical imaging, pathology, and radiology for enhanced diagnostic accuracy and clinical decision support
  • Integration of interpretability into AI-driven healthcare systems to enhance transparency, accountability, and user trust
  • Case studies and real-world applications demonstrating the utility and effectiveness of explainable AI models in clinical practice, biomedical research, and public health
  • Ethical considerations, regulatory compliance, and legal implications associated with the deployment of interpretable AI models in healthcare and biology
co-Chairs:
  • Naeem Ullah, University of Naples “Federico II” Naples, Italy
  • Prof. Javed Ali Khan, University of Hertfordshire, Hatfield, UK
  • Prof. Muhammad Shahid Anwar, University Seongnam-si, South Korea


SS-GAIMHS: Generative AI for Medical and Healthcare System

Over time, there has been increased development and interest in the use of generative AI. Even in the medical field, researchers have proposed and continue to propose the use of generative AI for various tasks. Patient records are hard to come by, medical data available to researchers are often few, unbalanced and incomplete. These types of problems can be addressed by using generative models for data augmentation. Generative AI is also the basis of modern chatbots, which can prove to be a useful support tool in the medical field. Other fields where the use of Generative AI is becoming more widespread are medical image reconstructions and enhancements, which for example can be resolution enhancement, noise reduction, occlusion removal, and more in medical images. An important issue for high-risk problems, such as the medical field, is the need to develop and use explainable AI models at the expense of black-box models; Generative AI models are not exempt from this obligation. The goal of this special session is to give researchers an opportunity to present and discuss their work proposing the use of generative AI for medical and health applications, while also providing some food for thought for future research directions.

TOPICS (but are not limited to):
  • Data Augmentation with Generative Models
  • Explainability and Interpretability in Generative AI
  • Generative Natural Language Models for Clinical Decision Support
  • Super Resolution, Colorization and Inpainting in Medical Imaging
  • Reconstruction and Denoising of Medical Resonance Images (MRI) or Computed Tomography (CT)
  • Generative AI for Patient Data Sharing Problems
  • Image segmentation in Medical Imaging
  • Weakly supervised approaches in Generative AI for Medical Systems
  • Image translation and domain adaptation of Medical Imaging
  • Image reconstruction from Medical instruments
  • Anomaly Detection in Medical Imaging using Generative AI
  • Issues and Challenges in Generative AI for Medical and Healthcare System
  • Generative AI for real-world Healthcare scenarios
co-Chairs:
  • Vincenzo Bevilacqua, ICAR-CNR, Italy
  • Prof. Angelo Ciaramella, University of Naples "Parthenope", Italy
  • Antonio Di Marino, ICAR-CNR, Italy
  • Dr. Emanuel Di Nardo, University of Naples "Parthenope", Italy




ICTS4eHealth Registration Fees:


Please carefully check the registration instructions at  https://2024.ieee-iscc.org/registration/

(all prices are displayed in euros)

Type Early Registration Late Registration
IEEE Member Conference Registration €380 €480
Non – IEEE Member Conference Registration €440 €540
Registration includes: access to the conference Sessions, Coffee breaks and Lunches during the realization days, welcome reception and gala dinner.
  • Each paper must have an AUTHOR REGISTRATION type (either IEEE Member or Non – IEEE Member)
  • Each Author Registration can associate a maximum of two papers.
  • Full papers cannot exceed 7 pages (6 pages + 1 extra page allowed for an additional fee);
  • One Extra Page: €90
  • Cancellation Policy: A cancellation fee of €120 will be applied. No cancellation will be allowed after May 31, 2024. In the impossibility to attend the conference, you can transfer the registration to another person.

  • Any administrative/bureaucratic/financial/registration/visa issue is directly managed by the mother conference ISCC.
    Therefore, authors can contact ISCC organizers to ask them any question about registration.

    Technical Program Committee

    TBA

    Best Paper Award

    A "Best Paper Award" Certificate will be conferred on the author(s) of a paper presented at the conference, selected by the Chairs based on scientific significance, originality and outstanding technical quality of the paper, as assessed also by the evaluations of the members of the Program Committee.



    Special Issues

    Authors of selected papers may be invited to submit extended versions of their papers for publication as full journal papers in special issues organized in prestigious indexed journals.

    Important Dates

    • Submission deadline for Special Session Proposals: February 26, 2024 - EXPIRED
    • Notification of acceptance for Special Session Proposals: February 29, 2024- EXPIRED

    Special Session proposals should be submitted via email to icts4eHealth@icar.cnr.it

    • Submission deadline for papers: March 30, 2024
    • Notification of paper acceptance: April 30, 2024
    • Submission of camera-ready papers: May 15, 2024
    • Registration: May 15, 2024

    All papers should be submitted via EDAS using https://edas.info/N32201

    Please, contact us for any questions regarding the submission of manuscripts.

    Venue

    ESIEE Paris, France

    The school of technological innovation.

    ESIEE Paris, n°1 of engineering schools in Ile-de-France. An engineering school specialised in digital, energy and environemental transitions.

    Address: Cité Descartes, 2 Bd Blaise Pascal, 93160 Noisy-le-Grand, Université Paris-Est Marne-la-Vallée

    Phone: (+33)(0)1 45 92 65 00

    Info:
    https://www.esiee.fr/en/informations/access-map

    Hotels:
    ibis Marne-la-Vallée Champs
    MOXY PARIS VAL D’EUROPE


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    Get in touch

    Contact Infomation

    icts4eHealth@icar.cnr.it