{
  "id": 9571,
  "url": "https://doi.org/10.1038/s41467-024-46043-y",
  "title": "Metabolomic machine learning predictor for diagnosis and prognosis of gastric cancer",
  "summary": "Gastric cancer (GC) represents a significant burden of cancer-related mortality worldwide, underscoring an urgent need for the development of early detection strategies and precise postoperative interventions. However, the identification of non-invasive biomarkers for early diagnosis and patient risk stratification remains underexplored. Here, we conduct a targeted metabolomics analysis of 702 plasma samples from multi-center participants to elucidate the GC metabolic reprogramming. Our machine ",
  "authors": "Yangzi Chen, Bohong Wang, Yizi Zhao, Xinxin Shao, Mingshuo Wang, Fuhai Ma",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2024-02-23T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:33:57.578Z",
  "source_slug": "openalex",
  "source_name": "OpenAlex",
  "source_homepage": "https://openalex.org",
  "ethics_ai_record_url": "https://ethics.ai/record/9571",
  "original_url": "https://doi.org/10.1038/s41467-024-46043-y",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}