AIMC Topic: Deep Learning

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Toward automatic prediction of EGFR mutation status in pulmonary adenocarcinoma with 3D deep learning.

Cancer medicine
To develop a deep learning system based on 3D convolutional neural networks (CNNs), and to automatically predict EGFR-mutant pulmonary adenocarcinoma in CT images. A dataset of 579 nodules with EGFR mutation status labels of mutant (Mut) or wild-type...

Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper addresses two key problems of skin lesion classification. The first problem is the effective use of high-resolution images with pretrained standard architectures for image classification. The second problem is the high-class imb...

Redundant feature pruning for accelerated inference in deep neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper presents an efficient technique to reduce the inference cost of deep and/or wide convolutional neural network models by pruning redundant features (or filters). Previous studies have shown that over-sized deep neural network models tend to...

Recent methodology progress of deep learning for RNA-protein interaction prediction.

Wiley interdisciplinary reviews. RNA
Interactions between RNAs and proteins play essential roles in many important biological processes. Benefitting from the advances of next generation sequencing technologies, hundreds of RNA-binding proteins (RBP) and their associated RNAs have been r...

Classification for invasion depth of esophageal squamous cell carcinoma using a deep neural network compared with experienced endoscopists.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Cancer invasion depth is a critical factor affecting the choice of treatment in patients with superficial squamous cell carcinoma (SCC). However, the diagnosis of invasion depth is currently subjective and liable to interobserver...

Statistical Approaches Based on Deep Learning Regression for Verification of Normality of Blood Pressure Estimates.

Sensors (Basel, Switzerland)
Oscillometric blood pressure (BP) monitors currently estimate a single point but do not identify variations in response to physiological characteristics. In this paper, to analyze BP's normality based on oscillometric measurements, we use statistical...

Deep Belief CNN Feature Representation Based Content Based Image Retrieval for Medical Images.

Journal of medical systems
Avascular Necrosis (AN) is a cause of muscular-skeletal disability. As it is common amongst the younger people, early intervention and prompt diagnosis is requisite. This disease normally affects the femoral bones, in order that the bones' shape gets...

Large-area, high-resolution characterisation and classification of damage mechanisms in dual-phase steel using deep learning.

PloS one
High performance materials, from natural bone over ancient damascene steel to modern superalloys, typically possess a complex structure at the microscale. Their properties exceed those of the individual components and their knowledge-based improvemen...

Testing a deep convolutional neural network for automated hippocampus segmentation in a longitudinal sample of healthy participants.

NeuroImage
Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal volumes manually is a time-consuming procedure, however, creating a need for automated segmentation m...