Artificial Intelligence and Machine Learning in Medical Microbiology Diagnostics

Event Description

This workshop addresses the growing importance of machine learning (ML) in enhancing diagnostic accuracy and efficiency in the field of molecular diagnostics. With advancements in technology and bioinformatics, ML has become a crucial tool in interpreting complex biological data. However, practical applications in routine diagnostics remain underutilized. This training aims to bridge the gap between theoretical ML models and their real-world applications in clinical settings.

Intended audience:

Interested medical microbiologists or infectious diseases experts (with some data handling experience) and data scientists (with microbiological knowledge) at different levels junior to senior.

Objectives:

• Equip participants with the ability to implement machine learning techniques in molecular diagnostic workflows.
• Gain knowledge of how to evaluate the effectiveness of machine learning models in clinical diagnostics.
• Apply machine learning models independently to address molecular diagnostic challenges.
• Understand the limitations and considerations of using machine learning in clinical environments.

Course coordinator:

Adrian Egli
University of Zurich
Switzerland

Organisers:

ESGMD - Genomic and Molecular Diagnostic
Swiss Society for Microbiology (SSM)

Accreditation:

The ESCMID Education team will apply for accreditation to the European Accreditation Council for Continuing Medical Education (EACCME®)

Certification:

Course organisers will monitor attendance. Only participants attending live sessions will be able to receive the certification.

Course Venue:

Institute of Medical Microbiology
Gloriastrasse 30, 8006 Zürich
Switzerland

Accommodation:

Not Included
 

Downloads

• Programme

Registration Fees

The registration fee includes access to the full course and planned activities.

The ESCMID Attendance Grant does not cover travel and accommodation expenses.