Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry
Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identification and antimicrobial resistance prediction. However, their deployment across institutions remains limited by domain shift, as acquisition-specific variability often leads models to capture technical artifacts rather than transferable biological information. Existing representation learning approaches primarily address this problem through statistic
Record details
Published: 8 August 2026
Source: arXiv cs.LG
Category: Research
Topics: Healthcare · Biotech
Retrieved: 11 August 2026
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ethics.ai (8 August 2026), “Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry,” evidence record 18332, https://ethics.ai/record/18332 (originally published by arXiv cs.LG).
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