AIMC Topic: Pattern Recognition, Automated
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Classification of acute lymphoblastic leukemia using deep learning.
Microscopy research and technique
Oct 23, 2018
Acute Leukemia is a life-threatening disease common both in children and adults that can lead to death if left untreated. Acute Lymphoblastic Leukemia (ALL) spreads out in children's bodies rapidly and takes the life within a few weeks. To diagnose A...
Machine-learning-based automatic identification of fetal abdominal circumference from ultrasound images.
Physiological measurement
Oct 22, 2018
OBJECTIVE: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated...
A fully convolutional two-stream fusion network for interactive image segmentation.
Neural networks : the official journal of the International Neural Network Society
Oct 21, 2018
In this paper, we propose a novel fully convolutional two-stream fusion network (FCTSFN) for interactiveimage segmentation. The proposed network includes two sub-networks: a two-stream late fusion network (TSLFN) that predicts the foreground at a red...
On the robustness of real-time myoelectric control investigations: a multiday Fitts' law approach.
Journal of neural engineering
Oct 19, 2018
OBJECTIVE: Real-time myoelectric experimental protocol is considered as a means to quantify usability of myoelectric control schemes. While usability should be considered over time to assure clinical robustness, all real-time studies reported thus fa...
Unsupervised and real-time spike sorting chip for neural signal processing in hippocampal prosthesis.
Journal of neuroscience methods
Oct 16, 2018
BACKGROUND: Damage to the hippocampus will result in the loss of ability to form new long-term memories and cognitive disorders. At present, there is no effective medical treatment for this issue. Hippocampal cognitive prosthesis is proposed to repla...
A Survey on Machine Learning Approaches for Automatic Detection of Voice Disorders.
Journal of voice : official journal of the Voice Foundation
Oct 11, 2018
The human voice production system is an intricate biological device capable of modulating pitch and loudness. Inherent internal and/or external factors often damage the vocal folds and result in some change of voice. The consequences are reflected in...
Social Touch Gesture Recognition Using Convolutional Neural Network.
Computational intelligence and neuroscience
Oct 8, 2018
Recently, social touch gesture recognition has been considered an important topic for touch modality, which can lead to highly efficient and realistic human-robot interaction. In this paper, a deep convolutional neural network is selected to implemen...
Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.
NeuroImage
Oct 6, 2018
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...
A semi-supervised deep learning method based on stacked sparse auto-encoder for cancer prediction using RNA-seq data.
Computer methods and programs in biomedicine
Oct 5, 2018
BACKGROUND AND OBJECTIVE: Cancer has become a complex health problem due to its high mortality. Over the past few decades, with the rapid development of the high-throughput sequencing technology and the application of various machine learning methods...
Male
Diagnosis, Computer-Assisted
Deep Learning
Lung Neoplasms
Sequence Analysis, RNA
Gene Expression Regulation, Neoplastic
Reproducibility of Results
Humans
Stomach Neoplasms
Software
False Positive Reactions
Algorithms
Breast Neoplasms
Supervised Machine Learning
Female
RNA
Pattern Recognition, Automated
Chemical crystal identification with deep learning machine vision.
BMC research notes
Oct 5, 2018
OBJECTIVE: This study was carried out with the purpose of testing the ability of deep learning machine vision to identify microscopic objects and geometries found in chemical crystal structures.
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