Speaker:
Adrian Egli, MD PhD, FAMH, University of Zurich
During this activity, learners will review:
*How artificial intelligence (AI) significantly enhances accuracy and efficiency in diagnostic microbiology
*Advanced language models, including ChatGPT, effectively support pre-analytical decision-making
* Customized AI tools improve detection of antimicrobial resistance (AMR), complementing expert interpretations
* Machine learning analysis of MALDI-TOF MS spectra shows potential for rapid AMR prediction
* AI-driven imaging and analytics reliably automate routine bacterial identification
* Integration of AI with genomic sequencing technologies offers promising strategies for predicting complex resistance mechanisms
Current Topics in Pathology 2024