{
  "id": 18332,
  "url": "https://arxiv.org/abs/2608.08182v1",
  "title": "Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry",
  "summary": "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",
  "authors": "Alejandro L. García-Navarro, Carlos Sevilla-Salcedo, Belén Rodríguez-Sánchez, Vanessa Gómez-Verdejo",
  "category": "research",
  "topics": "healthcare,biotech",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-08T15:19:53.000Z",
  "fetched_at": "2026-08-11T05:10:37.351Z",
  "source_slug": "arxiv-cslg",
  "source_name": "arXiv cs.LG",
  "source_homepage": "https://arxiv.org/list/cs.LG/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/18332",
  "original_url": "https://arxiv.org/abs/2608.08182v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}