Artificial intelligence improves risk stratification for breast cancer recurrence and mortality in women exposed to pesticides: a call for reassessment of stratification criteria - Takeaways - MDSpire

Artificial intelligence improves risk stratification for breast cancer recurrence and mortality in women exposed to pesticides: a call for reassessment of stratification criteria

  • By

  • Isabella Cristina Cazagranda

  • Daniel Rech

  • Stefania Tagliari de Oliveira

  • Fernanda Mara Alves

  • Carolina Panis

  • Guilherme Ferreira Silveira

  • June 3, 2026

  • 0 min

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  • 1

    Machine learning techniques improve diagnostic accuracy and treatment efficacy in breast cancer by analyzing patient history data.

  • 2

    Pesticide exposure is a significant risk factor for breast cancer recurrence and mortality, yet it is not included in current Brazilian guidelines.

  • 3

    The study utilized machine learning algorithms on data from 427 women to predict breast cancer outcomes, incorporating pesticide exposure as a risk factor.

  • 4

    Incorporating pesticide exposure improved the predictive quality of the best machine learning model by 24.12%, highlighting its importance.

  • 5

    The findings advocate for the reevaluation of breast cancer risk stratification standards to include pesticide exposure, particularly in farming regions.

Original Source(s)

Artificial intelligence improves risk stratification for breast cancer recurrence and mortality in women exposed to pesticides: a call for reassessment of stratification criteria

  • by Isabella Cristina Cazagranda, Daniel Rech, Stefania Tagliari de Oliveira, Fernanda Mara Alves, Carolina Panis, Guilherme Ferreira Silveira

  • June 3, 2026

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