AIMC Topic: Neural Networks, Computer

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Convolutional neural network-based computer-aided diagnosis in Hiesho (cold sensation).

Computers in biology and medicine
Hiesho (cold sensation) is a worldwide health problem primarily occurring in women. Females who suffered from Hiesho reported cold feeling at the extremities, which was also related to other chronic diseases. However, the diagnosis of Hiesho is still...

Towards bi-directional skip connections in encoder-decoder architectures and beyond.

Medical image analysis
U-Net, as an encoder-decoder architecture with forward skip connections, has achieved promising results in various medical image analysis tasks. Many recent approaches have also extended U-Net with more complex building blocks, which typically increa...

A hybrid deep learning model for forecasting lymphocyte depletion during radiation therapy.

Medical physics
PURPOSE: Recent studies have shown that severe depletion of the absolute lymphocyte count (ALC) induced by radiation therapy (RT) has been associated with poor overall survival of patients with many solid tumors. In this paper, we aimed to predict ra...

Impact of the training loss in deep learning-based CT reconstruction of bone microarchitecture.

Medical physics
PURPOSE: Computed tomography (CT) is a technique of choice to image bone structure at different scales. Methods to enhance the quality of degraded reconstructions obtained from low-dose CT data have shown impressive results recently, especially in th...

Classification of breast cancer with deep learning from noisy images using wavelet transform.

Biomedizinische Technik. Biomedical engineering
In this study, breast cancer classification as benign or malignant was made using images obtained by histopathological procedures, one of the medical imaging techniques. First of all, different noise types and several intensities were added to the im...

Speeding up the Topography Imaging of Atomic Force Microscopy by Convolutional Neural Network.

Analytical chemistry
Atomic force microscopy (AFM) provides unprecedented insight into surface topography research with ultrahigh spatial resolution at the subnanometer level. However, a slow scanning rate has to be employed to ensure the image quality, which will largel...

DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

Journal of chemical information and modeling
In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of simila...

The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale's 18th problem.

Proceedings of the National Academy of Sciences of the United States of America
Deep learning (DL) has had unprecedented success and is now entering scientific computing with full force. However, current DL methods typically suffer from instability, even when universal approximation properties guarantee the existence of stable n...

Classification of Underwater Target Based on S-ResNet and Modified DCGAN Models.

Sensors (Basel, Switzerland)
Underwater target classification has been an important topic driven by its general applications. Convolutional neural network (CNN) has been shown to exhibit excellent performance on classifications especially in the field of image processing. Howeve...

Investigating the Impact of Information Sharing in Human Activity Recognition.

Sensors (Basel, Switzerland)
The accuracy of Human Activity Recognition is noticeably affected by the orientation of smartphones during data collection. This study utilized a public domain dataset that was specifically collected to include variations in smartphone positioning. A...