Tracks & Topic


The Global Summit on Digital Health and Telemedicine of AI2SD Symposium Serie

The conference GFT-AIML'2020 presents the advances and innovative approaches describing that provide intelligent solutions in Digital Health and Telemedicine through presentations, interactive exhibits, posters, art installations and performances. Specifically, it welcomes mature work papers on:


GFT-AIML'2020 will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects.
The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of AI and Machine Learning.


★ Digital Health ★ Digital imaging ★ Fostering ongoing culture change in healthcare ★ Patient staff engagement and culture change ★ Data driven decision making in the Healthcare ★ Artificial Intelligence against COVID-19 ★ The Internet of Medical Things (IoMT) ★ Virtual and augmented reality in digital health ★ Future of Telemedicine ★ Emerging trends and opportunities in digital health market ★ Visions and Strategies for Virtual care services ★ Current Challenges of Digitalization in Healthcare Industry ★Blockchain – The New Trust Code for Digital Health Workflows ★AI Algorithms for health image processing ★ Artificial Intelligence Tools and Application in health ★ Automatic Control ★ Bioinformatics ★ Computer Vision and Speech Understanding ★ Data Mining and Machine Learning Tools ★ Fuzzy Logic ★ Heuristic and AI Planning Strategies and Tools ★ Hybrid Intelligent Systems ★ Information Retrieval ★ Intelligent System Architecture ★ Knowledge Representation in healthcare system ★ Knowledge-based Healthcare Systems ★ Multimedia & Cognitive Informatics ★ Natural Language Processing ★ Neural Networks ★ Parallel Processing ★ Pattern Recognition ★ Pervasive Computing and Ambient Intelligence ★ Programming Languages ★ Reasoning and Evolution ★ Recent Trends and Developments ★ Robotics ★ Semantic Web Techniques and Technologies ★ Soft computing theory and Applications ★ Software & Hardware Architectures ★ Web Intelligence Applications & Search ★ Learning Methods and analysis ★ Learning Problems ★ Machine Learning ★ Deep Learning ★ Hardware, Robotics & Electronics ★ Reinforcement Learning ★ Natural Language Processing ★ Computer Networks and Communications ★ Computer Vision
Track-01: Data driven decision making in the Healthcare

Analytics have proven very important for any business decisions, providing decision makers with important and relevant facts, making decisions clearer and more confident. The healthcare industry is no different, where analytics have been proven very *effective in improving clinical, financial, and operational performance. It was also reported that clinical areas have the highest overall success rate, with 78%. The use of analytics drives down readmission rates, improves patient outcome improvements, and aids in infection control and reduction.

Track-02: Artificial Intelligence in the Healthcare management

Artificial intelligence plays a critical role in the Healthcare management, including areas like pandemic detection, vaccine development, thermal screening, facial recognition with masks, and analyzing CT scans. Non-Contact infrared thermometers and other kinds of thermal screening systems use a variety of methods to determine the temperature of objects like humans. AI can quickly parse through many people at once to identify people with high temperatures. This can help to identify symptomatic individuals. Deep learning systems in facial recognition technology have improved enough that they can identify individuals with masks with accuracy of up to 95%. Even though large numbers of people are wearing masks, facial recognition is not concerned with whether or not they are wearing masks. Human error is a problem in CT scan analysis.

Track-03: The Internet of Medical Things (IoMT)

Consider your most recent healthcare interaction. It likely involved some sort of medical device or equipment — a blood pressure monitor, a continuous glucose monitor, maybe evens an MRI scanner. Today’s internet-connected devices are being designed to improve efficiencies, lower care costs and drive better outcomes in healthcare. As computing power and wireless capabilities improve, organizations are leveraging the potential of Internet of Medical Things technologies. With their ability to collect, analyse and transmit health data, IoMT tools are rapidly changing healthcare delivery. For patients and clinicians, these applications are playing a central part in tracking and preventing chronic illnesses — and they’re poised to evolve the future of care.

Track-04: Digital Health

It is the form of technologies deals with health, healthcare, society to frame the productivity of healthcare delivery and generate medicines more personalized and uniquely. The wide scopes of digital health consist of healthcare information technology(IT),devices that are wearable, mobile health (mHealth), telehealth and telemedicine, and personalized medicine. Patients and customers can use digital health to improve and manage the tracking of health and wellness and similar activities. Digital fitness technology encompass both hardware and software answers and services, including telemedicine, wearable devices, augmented reality, and digital reality. Generally, virtual fitness interconnects fitness structures to enhance using computational technology, clever devices, computational evaluation techniques, and verbal exchange media to aid healthcare professionals and their sufferers manipulate ailments and fitness risks, in addition to sell fitness and wellbeing.
- Telemedicine
- Wearable technology
- Augmented and virtual reality
- Innovation cycle
- International Standards

Track-05: Metaverse in Healthcare – New Era is Coming True

For many decades, the delivery of care has needed physical interaction between a patient and doctors. However the digital health solutions square measure currently on the cusp of Associate in Nursing unprecedentedly larger and a lot of voluminous type of AR& VR technology. (Virtual and augmented reality in digital health )
Augmented reality is one of the most promising digital health technologies at present. Augmented reality is the use of displays, cameras, and sensors to overlay digital information onto the real world. In contrast to Virtual reality (VR), which creates an entirely new world, AR allows us to bring the most useful information from the digital realm into our perception of the environment around us. AR is not a new concept, but over the last few years, advances in camera and sensor technology and AR-focused software research have made it practical — we’re still in the early stages of the AR revolution, but this year and into the future, we can expect to see an explosion of AR devices and applications enter the market. While increased reality technology holds limitless prospects within the care field, it should be developed in an exceedingly means that doesn't transcend the relationship between the patient and the doctor.

Track-7: Digital Medical Imaging

Digital Medical Imaging are the Images are stored using electronic media such as digital magnetic tape or other media. Digital medical imaging often allows doctors to make a diagnosis without invasive testing. Another form of digital medical imaging is used in breast thermography diagnostic testing. Digital imaging/morphology makes use of digital images and software algorithms to classify hematological cells, such as leukocytes and red blood cells. Digital technology allows for remote access to radiographic images. Remote access to images relieves radiologists of the requirement of being physically in the hospital at all times. The limitations of teleradiology are generally related to technology such as remote access, network speed and file size. There are differnet types of Medical Imaging Technologies.
MRI. An MRI, or magnetic resonance imaging, is a painless way that medical professionals can look inside the body to see your organs and other body tissues.
- CT Scan.
- PET/CT.
- Ultrasound.
- X-Ray.
- Arthrogram.
- Myelogram.
- Women's Imaging.

Heuristic search for Medical Data

A Heuristic is a technique to solve a problem faster than classic methods, or to find an approximate solution when classic methods cannot. This is a kind of a shortcut as we often trade one of optimality, completeness, accuracy, or precision for speed. A Heuristic (or a heuristic function) takes a look at search algorithms. At each branching step, it evaluates the available information and makes a decision on which branch to follow. It does so by ranking alternatives. The Heuristic is any device that is often effective but will not guarantee work in every case (data-flair.training).

Special Sessions

The conference is seeking submissions related to the following conference topics : all aspects of Digital Health, and approaches to computational intelligence and Data Sciences for medical area. Other related topics will also be considered.


Artificial Intelligencee


Machine Learning


Data Sciences


Computational Intelligence

About GS DHT-AI2SD Health Sumposium Serie

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Email: mezziyyani@uae.ac.ma