Machine learning for chemotherapy decision-making in breast cancer using large language model - Takeaways - MDSpire

Machine learning for chemotherapy decision-making in breast cancer using large language model

  • By

  • Md Serajun Nabi

  • Dema Yuden

  • Thinley Yeshey Choden

  • S. M. Asiful Islam Saky

  • Hasanul Bannah

  • Md Sabbir Hossen

  • Mohammad Faizal Ahmad Fauzi

  • Hezerul Bin Abdul Karim

  • July 6, 2026

  • 0 min

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  • 1

    A hybrid framework combining machine learning, causal reasoning, and large language models aims to enhance chemotherapy decision-making in breast cancer.

  • 2

    The Random Forest classifier achieved an AUC of 0.91, outperforming baseline machine learning models in predicting chemotherapy benefits.

  • 3

    Causal analysis identified patient groups where chemotherapy could be deprioritized, highlighting heterogeneous treatment benefits.

  • 4

    GPT-4 demonstrated moderate agreement with the Random Forest model while providing clinically relevant rationale for treatment decisions.

  • 5

    The proposed framework integrates predictive modeling and rationale generation to improve personalized and transparent chemotherapy recommendations.

Original Source(s)

Machine learning for chemotherapy decision-making in breast cancer using large language model

  • by Md Serajun Nabi, Dema Yuden, Thinley Yeshey Choden, S. M. Asiful Islam Saky, Hasanul Bannah, Md Sabbir Hossen, Mohammad Faizal Ahmad Fauzi, Hezerul Bin Abdul Karim

  • July 6, 2026

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