{
  "id": 19178683,
  "title": "Leave-One-Out-Cross-Validation Based Machine Learning Algorithms for Efficient, Scalable, and Robust Prediction of Artemisinin Resistance in Plasmodium falciparum Kelch13 mutants.",
  "url": "https://urgent.news/2026/11/09/leave-one-out-cross-validation-based-machine-learning-algorithms-for",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-09T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.11.05.764763v1?rss=1"
  },
  "original_language": "en",
  "account": "The emergence of resistance to frontline artemisinin derivatives in Plasmodium falciparum poses a significant threat to global malaria control efforts. Assessing the ART-sensitive (ART-S) or ART-resistant (ART-R) nature of parasite strains with Kelch13 (K13) mutations is currently a time-consuming process. The ring-survival assay (RSA), a gold standard for ex vivo laboratory adaptation, often fails to accurately predict clinical ART-responsiveness, making it unsuitable for quickly identifying novel K13 variants. AI-derived models, however, show promise in screening 100 K13 variants within hours, enabling rapid near-real-time prediction of ART-S/R status. To achieve this, researchers have engineered a panel of forty representative K13 variants by computing their relative deviations from the wild-type K13 across ten physicochemical and structural descriptors. These descriptors capture mutation-induced changes in folding, stability, and solvent exposure, providing a compact feature set that can be used to train and validate an AI classifier for predicting resistance.",
  "summary": "Emerging Plasmodium falciparum resistance to frontline artemisinin (ART) derivatives threatens global malaria control efforts. Current protocols assigning ART-sensitive (ART-S) or -resistant (ART-R) phenotypes to parasite strains with Kelch13 (K13) mutations remain time-intensive for real-time surveillance. Ring-survival assay (RSA), an ex vivo gold standard mandates laboratory-adaptation under…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}