{
  "id": 3059315,
  "title": "Cooperative Modular Representation Learning for Lung Adenocarcinoma Survival Prediction from Transcriptomic and Clinical Data",
  "url": "https://urgent.news/2026/08/24/cooperative-modular-representation-learning-for-lung-adenocarcinoma",
  "topic": "science",
  "section": "Science",
  "published": "2026-08-24T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.08.22.746396v1?rss=1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Accurate prognosis in lung adenocarcinoma (LUAD) requires integration of high-dimensional transcriptomic profiles with compact but clinically stable patient covariates. Naive fusion strategies allow the high-variance RNA-seq modality to dominate learned representations, suppressing clinical signal. We present Cooperative Modular Representation Learning (CMRL), an uncertainty-gated multimodal…",
  "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."
}