Introduction to AI and Machine Learning for Biomedical Research

11 October to 8 November 2021
Vlaamse AI Academie

Become familiarized with the basic concepts of machine learning and gain insight into current biomedical research topics that apply these techniques and the possibility of related ethical issues.

Huge amounts of data are available today for biomedical research. These data arise in different forms like images, omics-data, electronic medical files… Machine Learning algorithms can help researchers to find patterns, classify the data or help to make well-founded decisions, based on these data. Typical examples are the analysis of CT scans for cancer diagnoses or the identification of the proper treatment for MS patients. 

Objectives

  • You learn about the possibilities offered by artificial intelligence, and about some important concerns when applying them.
  • You’re able to assess if these AI techniques might be valuable for your research, or not.
  • You get familiarised with the basic terminology so as to better convey your biomedical research problem to an AI expert.

Programme

1. Theory (10h)

We look into the theoretical concepts and illustrate them with relevant examples.

  • Monday 11 October 2021
    Module 1 – 13.00-14.00h: Basics of Machine Learning (prof. dr. Jefrey Lijffijt – UGent)
    Module 2 – 14:15-16:15h: Supervised Learning (prof. dr. Jef Vandemeulebroucke – VUB)
  • Thursday 14 October 2021
    Module 3 – 13:00-15:00h: Unsupervised Learning (prof. dr. Celine Vens – KU Leuven)
  • Monday 18 October 2021
    Module 4 – 13:00-15:00h: Deep Learning and Neural Networks (dr. Joris Roels – VIB/UGent)
  • Thursday 21 October 2021
    Module 5 – 13:00-15:00h: Reinforcement Learning (prof. dr. Pieter Libin – AI Lab VUB)

2. Use cases (4h)

Researchers in the biomedical field present their research and the use of AI techniques.

  • Thursday 4 November 2021
    Module 6 – 13:00-15:15h: Use cases from the biomedical sector (part 1)
    • Yvan Saeys (UGent): Machine Learning challenges for single-cell biology
    • Liesbet Peeters (UHasselt): Multiple Sclerosis as a use case to show how AI an real world data transform our healthcare system
    • Alexandre Arnould & Melanie Nijs (KU Leuven): Dimensionality reduction for (multi-)omics data
    • Walter Daelemans (UAntwerpen): Biomedical and Clinical Natural Language Processing
    • Pieter Libin (AI Lab VUB): Deep Reinforcement Learning for Epidemic Policy Control
    • Ilse Vermeulen (UCLL): ASTMApping, localisation of respiratory hot-spots for asthmatic patients in an urban context through Citizen Science and low-cost sensor technology
  • Monday 8 November 2021
    Module 7 – 13:00-15:15: Use cases from the biomedical sector (part 2)
    • Kris Laukens (UAntwerpen): AI for the prediction of adaptive immune response to infection or vaccination
    • Axel Geysels (KU Leuven): 2D-segmentation models for ultrasonic images to automate the detection of ovarian cancer
    • Alexander Lemm (Amazon AWS): Introduction to AI/ML based biomedical research on AWS
    • Tamas Madl (Amazon AWS): Deep-dive into an AI/ML based research project: Munich Leukemia Lab
    • Peter De Jaeger (AZ Delta): AI applications today and the road towards a learning hospital
    • Nikolay Manyakov (Janssen Pharmaceutical Company): Data science applications in clinical trials

3. Challenges & ethical issues (2h) 

Challenges in collecting and processing data and possible ethical issues when using AI.

  • Monday 15 November
    Module 8 – 13:00-15:15h: Data management and ethics
    • Patrick De Mazière (UCLL)
    • Bart Vannieuwenhuyse (J&J)

Lecturers

Each module is thought by an expert from a relevant AI domain, and with expertise in biomedical research.

Course material

Slides + literature list

Interesting background information

  • Deep medicine: How Artificial Intelligence can make Healthcare Human again – Eric Topol
  • Inspiring online course: Elements of AI

After this course

The VIB offers several hands-on courses where you can train yourself in AI and machine learning techniques:

Cancellation and no-show policy

Are you unable to attend this course after all?  

Cancellation is free of charge up to 5 days before the start of the activity with a valid reason. In case of no-show or late cancellation with no valid reason presented you will receive a warning. If no-show or cancellation happens a second time (within the context of another course) you won’t be allowed to register for any other activity/course by the Vlaamse AI Academy. 

a collaboration between all Flemish universities
in cooperation with

Practical

  • 11 October – 8 November 2021
  • Location: online
  • Contact: Laura Alonso
  • Language: English
  • Target audience: junior researchers (Ph.D., postdoc or equivalent) in (bio)medical research or related research fields.

Registration?

  • Prerequisites: no technical knowledge required
  • Price:
    • free for researchers out of Flemish universities
    • contact Laura Alonso for the prices out of the academic field in Flanders
  • Deadline: 4 October 2021
  • Certification: attendance certificate by Vlaamse AI Academie

registration closed