Article

Uncertainty-Aware Antimicrobial Resistance Prediction in E. coli and S. aureus Isolates Using Hybrid Bayesian Neural Networks

2026-02-11

Abstract excerpt

<title>Abstract</title> Background: Antimicrobial resistance (AMR) poses a critical global health threat. However, conventional detection methods still require up to 72 hours, leading to treatment delays. AI models trained on mass spectrometry data enable faster prediction, but current approaches often lack uncertainty estimation, cross-hospital generalization, and clear interpretability of their predictions....

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Literature Corpus work: a4d8c1f2-7786-54c9-a822-5b566af254ac
DOI: 10.21203/rs.3.rs-8732992/v1

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