AIMC Topic: Neural Networks, Computer

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[Effects of sample size and data augmentation on U-Net-based automatic segmentation of various organs].

Igaku butsuri : Nihon Igaku Butsuri Gakkai kikanshi = Japanese journal of medical physics : an official journal of Japan Society of Medical Physics

Deep learning for differentiating benign from malignant tumors on breast-specific gamma image.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Breast diseases are a significant health threat for women. With the fast-growing BSGI data, it is becoming increasingly critical for physicians to accurately diagnose benign as well as malignant breast tumors.

CTCNet: A CNN-Transformer Cooperation Network for Face Image Super-Resolution.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Recently, deep convolution neural networks (CNNs) steered face super-resolution methods have achieved great progress in restoring degraded facial details by joint training with facial priors. However, these methods have some obvious limitations. On t...

Upper Limb Movement Decoding Scheme Based on Surface Electromyography Using Attention-Based Kalman Filter Scheme.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Convolutional neural network (CNN)-based models are widely used in human movement decoding based on surface electromyography. However, they capture only the spatial information of the surface electromyography and lack prior knowledge of the system, r...

A Developed LSTM-Ladder-Network-Based Model for Sleep Stage Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Sleep staging is crucial for diagnosing sleep-related disorders. The heavy and time-consuming task of manual staging can be released by automatic techniques. However, the automatic staging model would have a relatively poor performance when working o...

ReRNet: A Deep Learning Network for Classifying Blood Cells.

Technology in cancer research & treatment
AIMS: Blood cell classification helps detect various diseases. However, the current classification model of blood cells cannot always get great results. A network that automatically classifies blood cells can provide doctors with data as one of the c...

Statistical and Machine Learning Methods for Discovering Prognostic Biomarkers for Survival Outcomes.

Methods in molecular biology (Clifton, N.J.)
Discovering molecular biomarkers for predicting patient survival outcomes is an essential step toward improving prognosis and therapeutic decision-making in the treatment of severe diseases such as cancer. Due to the high-dimensionality nature of omi...

DeepZ: A Deep Learning Approach for Z-DNA Prediction.

Methods in molecular biology (Clifton, N.J.)
Here we describe an approach that uses deep learning neural networks such as CNN and RNN to aggregate information from DNA sequence; physical, chemical, and structural properties of nucleotides; and omics data on histone modifications, methylation, c...

Human activity recognition for analyzing stress behavior based on Bi-LSTM.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Stress is one of the critical health factors that could be detected by Human Activity Recognition (HAR) which consists of physical and mental health. HAR can raise awareness of self-care and prevent critical situations. Recently, HAR used...