1st & 2nd Schools

From November 18 to November 22, 2024, Stichting Amsterdam UMC (AUMC) hosted two training activities, Schools 1 & 2, at Amsterdam, The Netherlands. The first School, entitled “Healthcare 4.0: Challenges and opportunities”, provided essential training on requirements, main challenges, and enabling technologies in Healthcare 4.0, including secure information handling, data analytics, AI in healthcare, and challenges related to the Internet of Medical Things (IoMT). The second School, entitled “3GPP architecture and introduction to the 6G enabling technologies towards Healthcare 4.0”, focused on the architecture of 3GPP, 6G requirements, technology enablers, and sustainability considerations for 6G networks that support Healthcare 4.0.

Both schools, delivered by our academic and industrial partners alongside invited experts, offered valuable skills to professionals and researchers working towards the future of healthcare technology.

All presented material can be obtained here.


1st School: Healthcare 4.0: Challenges and opportunities


Date

Speaker 

Title

Syllabus 

Monday 18th of November 2024

AUMC

Prof. Henk Marquering 

&

Dr. Praneeta Konduri

Requirements, main challenges and enabling technologies in Healthcare 4.0

  • What is healthcare 4.0? How does it differ from previous versions - evolution. 
  • Elements of Healthcare 4.0; AI, DTs, IoT, Robotics
  • Aims and of objectives of Healthcare 4.0
  • How did Healthcare 4.0 change stroke care? 
  • Assignments: role of ICT in Healthcare 4.0

TU Delft

Dr. Marcela Tuler

Secure information handling and ubiquitous access to the healthcare services

  • Privacy and Security in Healthcare 4.0.
  • Secure information exchange.
  • Privacy enhancing techniques.
  • Blockchain in healthcare

 

 

Tuesday 19th of November 2024

SUIT

Dr. Minas Pertselakis

Data analytics and AI in healthcare

  • What type of problems in healthcare can AI solve? What restrictions does GDPR bring to the table?
  • Data analytics: descriptive vs predictive, AI vs Machine learning. Examples.
  • Explainable AI in healthcare

MCS

Mr. Sai Chintha

Challenges of IoMT and the way forward

  • IoMT and the MCS ecosystem
  • Challenges in IoMT
  • AI and Data in Healthcare

 

 

 

 

 

Wednesday 20th of November 2024

MCS

Mr. Sai Chintha

Challenges of IoMT and the way forward

  • Data privacy methods
  • Low energy computing 
  • An application of AI for Pain estimation

CHAR

Prof. Andreas Pfeiffer

(online)

 

Prognostic and diagnostic tests for diabetes

 

  • Definition and Diagnostic criteria
  • Background: How is blood sugar regulated?
  • Pathological impact – why is dysregulated blood sugar a problem
  • Impact of Diabetes mellitus worldwide on healthcare systems
  • Use of wearables and digital devices in diabetes diagnostics and management – continuous glucose monitoring
  • Therapy – (and why do so many people want to take diabetes therapeutics?)

AUMC

Dr. Dave Bouman 

Connected ambulance

  • What is a connected ambulance?
  • Role of ICT in connected ambulance.


2nd School: 3GPP architecture and introduction to the 6G enabling technologies towards Healthcare 4.0


Date

Speaker 

Title

Syllabus 

Wednesday 20th of November 2024

ORAN

Dr. Lechoslaw Tomaszewski

3GPP architecture, its main components and path to 6G

  • Fundamentals of mobile networks
  • Evolution from 1G to 5G
  • 3GPP – how to search, read, and understand their documents; 3-stage standardization process; approach to releases
  • 3GPP 5G System – fundamental underlying pradigms
  • 3GPP 5G System – architecture, network functions, focus on Control Plane
  • 3GPP 5G System – User Plane and how the QoS is provided
  • 3GPP 5G System – procedures: fundamental ones, how to read and understand system procedures
  • 3GPP 5G System – a bit about RAN (bands and their propagation/capacity characteristics, time/frequency multiplexing + “channelisation” in 5G, uplink/downlink,  interference management, antenna systems – SISO/MISO/SIMO/MIMO, softwarisation + O-RAN and RAN splits)
  • 3GPP 5G System – what went wrong: drawbacks, wrong choices, gaps – why we are looking forward to having 6G?

Date

Speaker 

Title

Syllabus 

Thursday 21st of November 2024

AUTH

Dr. Agapi Mesodiakaki

6G requirements, technology enablers and challenges

  • Evolution of the mobile networks (from 0G  to 6G)
  • Present and future with numbers
  • 6G service requirements and KPIs/KVIs
  • 6G enabling  technologies
  • Challenges
  • Solutions

NOKIA

Dr. Ali Rezaki 

(online)

Sustainability aspects of 6G networks supporting H4.0

  • Sustainability terminology, concepts and methodologies,
  • Use case design for value outcomes with target setting, value indicators and assessments,
  • 6G technology enablers for sustainability,
  • From energy efficiency and savings to sustainability outcomes – a systems perspective.

LIU

Prof. Nikolaos Pappas

Semantic communications for massive IoMT

  • Motivation and current approaches towards semantics-aware goal-oriented communications
  • Measuring timeliness and freshness of information - an introduction to Age of Information (AoI)
  • Semantics beyond AoI
  • Real-time tracking and actuation
  • Applications:  Industrial IoT, semantic source coding, and autonomous systems
  • Future outlook of task-oriented and semantics-aware communication and networks

Date

Speaker 

Title

Syllabus 

 

 

 

 

 

 

Friday 22nd of November 2024

LU

Dr. Konstantinos Ntontin

 

Introduction to Multiple-Antenna Communications and Reconfigurable Intelligent Surfaces

 

  • Fading channels
  • Diversity combining
  • Beamforming
  • Spatial multiplexing
  • Multi-user multiple-antenna communications
  • Capacity
  • Reconfigurable intelligent surfaces

AUTH

Dr. Marios Gatzianas 

(online)

Fundamentals of Channel modeling

  • Mobile radio propagation channel
  • Classification of channel models
  • 3GPP channel models

HU

Dr. Holger Schlingloff

(online)

 

 

 

 

Quality assurance of AI in healthcare

  • How can we achieve trust in AI solutions which is necessary for healthcare applications?
  • Types of related applications
  • Development of different technologies for the verification and testing of deep learning, different application areas, strengths and limitations. 
  •  Summarize recent results
  •  Directions for further research.