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Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma

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Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma

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A meta-learning approach for genomic survival analysis

Model-informed machine learning for multi-component T2 relaxometry

Vision based pixel-level bridge structural damage detection using a link ASPP network

The use of texture-based radiomics CT analysis to predict outcomes in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy

Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness

Neural Scene Decomposition for Multi-Person Motion Capture

RANKL Signaling Sustains Primary Tumor Growth in Genetically Engineered Mouse Models of Lung Adenocarcinoma

Mean-Field methods for Structured Deep-Learning in Computer Vision

A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT

Role of RIP4 in lung adenocarcinoma differentiation