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Machine learning reveals why cancer trials fall short in real-world patients

  • A new study shows that cancer trials often fail to represent real-world patients, leading to lower survival outcomes than reported in randomized controlled trials .
  • The study found that high-risk patients experienced survival benefits that were 62% lower than RCT estimates, highlighting the gap in treatment effectiveness.
  • Researchers developed an AI platform called TrialTranslator to help assess patient benefits from clinical trials, focusing on prognosis rather than strict eligibility criteria.
  • The study suggests improving representation of high-risk groups in trials and emphasizes the potential of AI to enhance precision medicine in oncology.
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Scienmag: Latest Science and Health News broke the news in on Wednesday, January 8, 2025.
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