ESCMID: ESGAID

Aims and objectives

The study group will cover the following major topics: AI, machine learning, digital innovation, data and methodological standardization and interoperability. We will address multiple themes:

Applications of AI and data including to clinical microbiology, infectious diseases, antimicrobial stewardship, infection prevention and control, surveillance, hospital epidemiology, and public health.
Best practice in developing new AI approaches including study design, reporting, and applications of specific methodologies, e.g. classical machine learning methods, deep learning, interpretable methods, addressing bias, federated learning, large language models, data sharing, equity etc.
Data access, governance, standardization, and interoperability to develop collaborations to assemble and share data effectively and at scale.
Implementation standards and best practice to support AI and data platform development, decision support systems, safety monitoring, and oversight of real-world implementations of AI.
Public and clinical engagement
Training and capacity building across a wide spectrum of pre-existing capabilities to support interpreting results, evaluating tools, understanding methods, and developing new approaches from high- to low- and middle-income settings.

Within the data theme the study group will focus on FAIR use of data (Findability, Accessibility, Interoperability, and Reusability). We aim to establish a framework for lab-data exchange in cooperation with experts involved in the European Health Data Space (EHDS) and other expert groups.

Activities and resources

CMID-Synergy Project Initiation Document Objectives, Scope and Organization

The Open-Source CMID Laboratory & Stewardship Platform - short name CMID-Synergy, synonym CMID-Nexus - is designed from the ground up by Clinical Microbiology and Infectious Diseases Specialists[1] for optimal patient care in this field and will serve as:

A general standardized and interoperable Clinical Microbiology Information System
A diagnostic test repertoire and ABx guide, standardized and dynamic
An integrated platform for Diagnostic, Antimicrobial and Infection Prevention Stewardship
A real time surveillance engine

By open-source we mean that all relevant project notes will be publicly shared in a living document from beginning to end. This enables the wider CMID community to learn from our experience (breakthroughs and mistakes) and build upon the framework.

CMID-Synergy Project Initiation Document

How ready are we to use artificial intelligence in our fight against antimicrobial resistance? An ESGAID and EAAS perspective.

Giacobbe DR, Ahmad R, Akilli FM, Ascandari A, Eyre DW, Gallardo-Pizarro A, Garcia-Vidal C, Lopes BS, Lyutsova E, Rakhimov R, Rizzo A, Rohde H, Sadeghi Z, Schweitzer V, Tartari E, Torres-Sangiao E, Guerrero-López A; European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group on Artificial Intelligence and Digitalisation (ESGAID) and the ESCMID Antimicrobial Resistance (AMR) Action Subcommittee (EAASC). Expert Rev Anti Infect Ther. 2026 Jan;24(1):39-61

Go to publication

AI for antimicrobial stewardship

10 February 2026 at 16:00 CET

Go to webinar

AI for diagnostics in clinical microbiology

NEW DATE: 06 February 2026 at 15:00 CET

Go to webinar

Research-Driven Standardisation: Common Data Models (OMOP)

27 January 2026 at 16:00 CET

Go to webinar

Technical Frameworks for Standardization: Exploring FHIR for ID and CM Specialists

05 December 2025 at 15:00 CET