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Updated: Nov 1, 2025
09:57
Characterizing Microbiome Dynamics – Flow Cytometry Based Workflows from Pure Cultures to Natural Communities
Published on: July 12, 2018
12.2K
Digital microbiology
A Egli1, J Schrenzel2, G Greub3
1Clinical Bacteriology and Mycology, University Hospital Basel, Basel, Switzerland; Applied Microbiology Research, Department of Biomedicine, University of Basel, Basel, Switzerland.
Summary
Digitalization and machine learning will transform clinical microbiology labs. Understanding data handling is key to leveraging artificial intelligence and big data for improved diagnostics and workflows.
Area of Science:
- Microbiology
- Bioinformatics
- Clinical Diagnostics
Background:
- Digitalization and AI are reshaping future microbiology laboratory operations.
- Significant opportunities and challenges exist in digitalizing microbiological workflows.
- Effective use of big data, machine learning (ML), and artificial intelligence (AI) in clinical microbiology necessitates a deep understanding of data handling.
Purpose of the Study:
- To review key concepts in digital microbiology for microbiologists, clinicians, and data scientists.
- To provide practical examples of digital applications throughout the diagnostic process.
- To offer insights into the opportunities and challenges of digitalizing diagnostic processes.
Main Methods:
- Literature review using PubMed.
- Search terms included digitalization, machine learning, artificial intelligence, and microbiology.
- Analysis of peer-reviewed literature.
Main Results:
- Digitalization presents opportunities and challenges in microbiological diagnostics.
- Key aspects of data structure, interoperability, and legal considerations are crucial.
- The review outlines pathways for implementing digital technologies in modern labs.
Conclusions:
- Digitalization and ML will profoundly impact daily laboratory routines.
- Identifying steps in the analytical process where digital technologies offer benefits is essential.
- Adapting staff education is critical to prepare for advances in digital microbiology.
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