[NFBCS] [CFP] [Extended Deadline] IEEE ICTS4eHealth 2024 - International Conference on ICT solutions for eHealth - Paris, France, June 26-29, 2024

[ICTS4eHealt2024]

[Apologies if you receive multiple copies of this CFP]

Dear colleagues,
We do hope this Call for Papers may be of your interest.
  
Yours sincerely,
IEEE ICTS4eHealth Conference Chairs
 
 
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4th Edition of IEEE International Conference on ICT Solutions for e-Health
ICTS4eHealth 2024
 
Paris, France, June 26-29, 2024
 
www.icts4ehealth.icar.cnr.it
 
in conjunction with the 29th IEEE Symposium on Computers and Communications (ISCC)
 
Submit your paper by using the link: https://edas.info/N32201

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MISSION:
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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.
 

TOPICS:
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- 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
- Cloud computing and AT
- 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
 
 
IMPORTANT DATES:
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- Submission deadline: April 13, 2024
- Notification of paper acceptance: May 07, 2024
- Submission of camera-ready papers: May 15, 2024
- Registration: May 15, 2024
 

PAPER SUBMISSION:
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Manuscripts should describe original work and should be no more than 7 pages for full papers and 4 pages for short papers 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 of 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 for 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.


SPECIAL SESSIONS:
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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.

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.

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.

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.

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


REGISTRATION FEES:
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IEEE Member Conference Registration:
- Early registration: €380
- Late registration:  €500

Non - IEEE Member Conference Registration:
- Early registration: €440
- Late registration:  €600

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.

 
BEST PAPER AWARD:
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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.
 

STEERING COMMITTEE:
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- Antonio Celesti, University of Messina, Italy;
- Ivanoe De Falco, ICAR-CNR, Italy;
- Giovanna Sannino, ICAR-CNR, Italy;
- Massimo Villari, University of Messina, Italy.


ORGANIZATION:
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General chair:
- Giovanna Sannino, ICAR-CNR, Italy.

Technical Program Co-Chairs:
- Alessio Catalfamo, University of Messina, Italy;
- Fabrizio Celesti, University of Siena, Italy;
- Ivanoe De Falco, ICAR-CNR, Italy.

Publicity Chair:
- Annamaria Ficara, University of Messina, Italy.

Honorary Chair: 
- Giuseppe De Pietro, Director of ICAR - CNR, Italy.

Please visit http://icts4ehealth.icar.cnr.it  for more information, and if you have any questions, kindly get back to us by sending an email to icts4eHealth at icar.cnr.it
 
Kind regards,
IEEE ICTS4eHealth 2024 Organization