This is a match-making section for JPIAMR 16th call -AMR diagnostics and surveillance 2023 (DISTOMOS).
Human Health
machine learning;artificial intellingence;AMR prediction;bloodstream infections;antimicrobial stewardship
We are a team of clinical microbiologists and researchers with experience in fast microbiology methods and artificial intelligence algorithms. We would like to cooperate with colleagues (microbiologists using MALDI-TOF, biostatistics and bioinformatics) interested by the development of machine learning models for AMR fast prediction based on multiple data sources.
The project aims to implement the microbiological diagnostic workflow for bloodstream infections by the development of artificial intelligence algorithms, based on machine learning, that integrate clinical and microbiological parameters including proteomic data obtained by MALDI-TOF MS, in order to obtain a fast AMR prediction.
Submitted on 2023-01-27 16:14:44
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