Development and validation of an explainable machine learning model for predicting postoperative pulmonary complications after lung cancer surgery: a machine learning studyResearch in context
Summary: Background: Early identification and prediction of postoperative pulmonary complications (PPCs) are vital for patient management in lung cancer (LC) surgery. However, existing predictive models often lack comprehensive validation and interpretability. This study aimed to develop and valida...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | EClinicalMedicine |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2589537025003189 |
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