AIMC Topic: Neural Networks, Computer

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Deep learning-enabled system for rapid pneumothorax screening on chest CT.

European journal of radiology
PURPOSE: Prompt diagnosis and quantitation of pneumothorax impact decisions pertaining to patient management. The purpose of our study was to develop and evaluate the accuracy of a deep learning (DL)-based image classification program for detection o...

Deep learning for World Health Organization grades of pancreatic neuroendocrine tumors on contrast-enhanced magnetic resonance images: a preliminary study.

International journal of computer assisted radiology and surgery
PURPOSE: The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision. The rarity of PNET often negatively affects the radiological application of deep learning algorith...

Automatic detection of contouring errors using convolutional neural networks.

Medical physics
PURPOSE: To develop a head and neck normal structures autocontouring tool that could be used to automatically detect the errors in autocontours from a clinically validated autocontouring tool.

Sensor Fault Detection and Diagnosis Method for AHU Using 1-D CNN and Clustering Analysis.

Computational intelligence and neuroscience
This paper presents a fault detection and diagnosis (FDD) method, which uses one-dimensional convolutional neural network (1-D CNN) and WaveCluster clustering analysis to detect and diagnose sensor faults in the supply air temperature ( ) control loo...

Self Multi-Head Attention-based Convolutional Neural Networks for fake news detection.

PloS one
With the rapid development of the internet, social media has become an essential tool for getting information, and attracted a large number of people join the social media platforms because of its low cost, accessibility and amazing content. It great...

Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data.

IEEE transactions on medical imaging
Prognostic tumor growth modeling via volumetric medical imaging observations can potentially lead to better outcomes of tumor treatment management and surgical planning. Recent advances of convolutional networks (ConvNets) have demonstrated higher ac...

Embedding topological features into convolutional neural network salient object detection.

Neural networks : the official journal of the International Neural Network Society
Salient object detection can be applied as a critical preprocessing step in many computer vision tasks. Recent studies of salient object detection mainly employed convolutional neural networks (CNNs) for mining high-level semantic properties. However...

Gated spiking neural network using Iterative Free-Energy Optimization and rank-order coding for structure learning in memory sequences (INFERNO GATE).

Neural networks : the official journal of the International Neural Network Society
We present a framework based on iterative free-energy optimization with spiking neural networks for modeling the fronto-striatal system (PFC-BG) for the generation and recall of audio memory sequences. In line with neuroimaging studies carried out in...

Towards early monitoring of chemotherapy-induced drug resistance based on single cell metabolomics: Combining single-probe mass spectrometry with machine learning.

Analytica chimica acta
Despite the presence of methods evaluating drug resistance during chemotherapies, techniques, which allow for monitoring the degree of drug resistance in early chemotherapeutic stage from single cells in their native microenvironment, are still absen...

Enhancing the security of patients' portals and websites by detecting malicious web crawlers using machine learning techniques.

International journal of medical informatics
INTRODUCTION: There is increasing demand for access to medical information via patients' portals. However, one of the challenges towards widespread utilisation of such service is maintaining the security of those portals. Recent reports show an alarm...