Correction: Development and validation of an interpretable machine learning model for venous thromboembolism risk prediction in patients with lung cancer: a real-world study - Takeaways - MDSpire
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Correction: Validation and Development of an Explainable Machine Learning Approach for Predicting Venous Thromboembolism Risk in Lung Cancer Patients: A Real-World Analysis

  • By

  • Frontiers Production Office

  • September 8, 2026

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  • 1

    A correction was issued for the P-values in Table 1 of a study on venous thromboembolism risk in lung cancer patients.

  • 2

    The corrected P-values for 'Anticoagulant' and 'Chemotherapy drugs' are both now reported as 1.000.

  • 3

    The statistical interpretation remains unchanged, indicating no significant differences between training and validation cohorts.

  • 4

    The correction does not affect the model construction, results, interpretation, or conclusions of the original article.

  • 5

    The article was published in Frontiers in Medicine, volume 13, and is available under the Creative Commons Attribution License.

Original Source(s)

Correction: Development and validation of an interpretable machine learning model for venous thromboembolism risk prediction in patients with lung cancer: a real-world study

  • by Frontiers Production Office

  • September 8, 2026

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