Development and validation of a machine learning model to evaluate survival in patients with newly diagnosed breast cancer with liver metastasis - Scorecard - MDSpire

Development and validation of a machine learning model to evaluate survival in patients with newly diagnosed breast cancer with liver metastasis

  • By

  • Yao Wang

  • Yu Yue

  • Xu-Chen Cao

  • June 16, 2026

  • 0 min

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Clinical Scorecard: Creation and assessment of a machine learning algorithm for predicting survival in patients with newly diagnosed breast cancer and liver metastases

At a Glance

CategoryDetail
Condition
Key MechanismsMachine learning algorithms for prognostic modeling (source needed)
Target Population
Care SettingOncology, specifically for metastatic breast cancer management (source needed)

Key Highlights

  • Development of a prognostic nomogram using SEER database data (2010–2021) (source needed)
  • Incorporation of ten prognostic variables into a multivariate Cox proportional hazards regression model (source needed)

Guideline-Based Recommendations

Diagnosis

    Management

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    Monitoring & Follow-up

    • R
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    Risks

      Patient & Prescribing Data

      Patients with breast cancer liver metastases from SEER database

      Prognostic model integrates demographic, clinicopathological, metastatic, treatment-related, and molecular factors

      Clinical Best Practices

      • Incorporate machine learning-based prognostic models for individualized survival prediction (source needed)

      Related Resources & Content

      Original Source(s)

      Development and validation of a machine learning model to evaluate survival in patients with newly diagnosed breast cancer with liver metastasis

      • by Yao Wang, Yu Yue, Xu-Chen Cao

      • June 16, 2026

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