Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

Wahyu Wulaningsih^1,2, Carmela Villamaria³, Abdullah Akram³, Janella Benemile³, Filippo Croce⁴, Johnathan Watkins⁵

¹The Royal Marsden, London, UK. wahyu.wulaningsih@nhs.net.

²Faculty of Life Sciences & Medicine, King's College London, London, UK. wahyu.wulaningsih@nhs.net.

³Modamast Pte Ltd, Singapore, Singapore.

⁴University Hospital of Wales, Cardiff, UK.

⁵Optellum Ltd, Oxford, UK. johnathan.watkins@optellum.com.

PubMed PMC DOI PDF

Abstract

BACKGROUND: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (CADx) models, and assess their diagnostic performance for predicting the risk of malignancy in computed tomography (CT)-detected pulmonary nodules. ME…

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