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Multimodal Deep Learning for Personalized Renal Cell Carcinoma Prognosis: Integrating CT Imaging and Clinical Data
The feature extractor module, based on the 3D CNN architecture, predicts the ISUP grade of renal cell carcinoma tumors linked to mortality rates from CT images.
Accurate Real-time Polyp Detection in Videos from Concatenation of Latent Features Extracted from Consecutive Frames
We propose an efficient feature concatenation method for a CNN-based encoder-decoder model without adding complexity to the model.
The End-to-End Molecular Communication Model of Extracellular Vesicle-based Drug Delivery
A closer look at nature has recently brought more interest in exploring and utilizing intra-body communication networks composed of cells as intrinsic, perfectly biocompatible infrastructures to deliver therapeutics.
Polyp Detection and Segmentation using Mask R-CNN: Does a Deeper Feature Extractor CNN Always Perform Better?
Automatic polyp detection and segmentation are highly desirable for colon screening due to polyp miss rate by physicians during colonoscopy, which is about 25%.
Automatic Colon Polyp Detection using Region based Deep CNN and Post Learning Approaches
Automatic detection of colonic polyps is still an unsolved problem due to the large variation of polyps in terms of shape, texture, size, and color, and the existence of various polyp-like mimics during colonoscopy.
