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

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

Frontiers In Medicine

Share

Original Source(s)

Frontiers In Medicine

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

Related Content

Frontiers In Immunology

Prognostic superiority of volumetric PET parameters (MTV and TLG) over SUV in advanced non-small-cell lung cancer: a systematic review and meta-analysis of univariate and multivariate evidence

by Jinwen Han, Hanxiang Zhang, Xianhong He, Zhimin Wang
August 25, 2026

Frontiers In Oncology

Safety and efficacy of drug-eluting beads versus conventional bronchial arterial chemoembolization for lung cancer: a systematic review and meta-analysis

by Zezhong Gong, Yali Liu, Yusheng Song, Xinghai Li, Yunfei Tian, Jing Li, Chaoyi Qi
July 21, 2026

The Pathologist

Molecular Diagnostics Go Mobile

A smartphone-linked fluorimeter detects infectious disease and cancer biomarkers in 10-minute assays

August 31, 2026
3 min