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Related Experiment Video

Updated: Sep 10, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Short-Term Prediction Model for Breast Cancer Risk Based on One Million Medical Records.

Ofer Feinstein1, Dan Ofer2, Eitan Bachmat3

  • 1The Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.

Clinical Breast Cancer
|August 23, 2025
PubMed
Summary
This summary is machine-generated.

This study developed a one-year breast cancer risk prediction model using electronic medical records (EMRs). The model, achieving an AUC-ROC of 0.85, can aid clinicians in early detection and decision-making for breast cancer.

Keywords:
Big dataCatBoostMachine learningRisk model

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Area of Science:

  • Oncology
  • Medical Informatics
  • Biostatistics

Background:

  • Despite advancements in breast cancer screening, many women are diagnosed with advanced-stage disease.
  • There is a need for accurate short-term breast cancer risk prediction models.

Purpose of the Study:

  • To develop a one-year breast cancer risk prediction model using readily available electronic medical record (EMR) data.
  • To support clinical decision-making in breast cancer risk assessment.

Main Methods:

  • Retrospective cohort study of 1,039,212 individuals from 1985-2021.
  • Utilized longitudinal EMR data including demographics, family history, lifestyle, medical history, and lab tests.
  • Employed CatBoost decision tree methodology and SHapley Additive exPlanations (SHAP) for model training and feature importance.

Main Results:

  • The prediction model achieved a high performance with an Area Under the ROC Curve (AUC-ROC) of 0.85.
  • Identified novel predictive features such as medications, systolic blood pressure, and TSH levels, in addition to age, surgical consultations, and breast biopsies.

Conclusions:

  • Electronic medical record (EMR) data can be effectively utilized to build accurate short-term breast cancer risk prediction models.
  • This model can assist clinicians in assessing and managing short-term breast cancer risk.