Enhanced Malignancy Prediction of Small Lung Nodules in Different Populations Using Transfer Learning on Low-Dose Computed Tomography

<b>Background:</b> Predicting malignancy in small lung nodules (SLNs) across diverse populations is challenging due to significant demographic and clinical variations. This study investigates whether transfer learning (TL) can improve malignancy prediction for SLNs using low-dose computed tomography...

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Auteurs principaux:	Jyun-Ru Chen, Kuei-Yuan Hou, Yung-Chen Wang, Sen-Ping Lin, Yuan-Heng Mo, Shih-Chieh Peng, Chia-Feng Lu
Format:	Artigo
Langue:	Inglês
Publié:	MDPI AG 2025-06-01
Collection:	Diagnostics
Sujets:	small lung nodule malignancy prediction population variations deep learning transfer learning
Accès en ligne:	https://www.mdpi.com/2075-4418/15/12/1460
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