AIMC Topic: Neural Networks, Computer

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Leveraging deep learning algorithms for synthetic data generation to design and analyze biological networks.

Journal of biosciences
The use of synthetic data is gaining an increasingly prominent role in data and machine learning workflows to build better models and conduct analyses with greater statistical inference. In the domains of healthcare and biomedical research, synthetic...

Deep-Learning Model Based on Convolutional Neural Networks to Classify Apnea-Hypopnea Events from the Oximetry Signal.

Advances in experimental medicine and biology
Automated analysis of the blood oxygen saturation (SpO) signal from nocturnal oximetry has shown usefulness to simplify the diagnosis of obstructive sleep apnea (OSA), including the detection of respiratory events. However, the few preceding studies ...

Low-dose CT noise reduction based on local total variation and improved wavelet residual CNN.

Journal of X-ray science and technology
BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposure. However, reducing radiation dose leads to considerable noise in the reconstructed image that can affect doctor's judgment.

Squamous Cell Carcinoma of Skin Cancer Margin Classification From Digital Histopathology Images Using Deep Learning.

Cancer control : journal of the Moffitt Cancer Center
OBJECTIVES: Now a days, squamous cell carcinoma (SCC) margin assessment is done by examining histopathology images and inspection of whole slide images (WSI) using a conventional microscope. This is time-consuming, tedious, and depends on experts' ex...

LCDAE: Data Augmented Ensemble Framework for Lung Cancer Classification.

Technology in cancer research & treatment
The only possible solution to increase the patients' fatality rate is lung cancer early-stage detection. Recently, deep learning techniques became the most promising methods in medical image analysis compared with other numerous computer-aided diagn...

Ensemble of diverse deep neural networks with pseudo-labels for repayment prediction in social lending.

Science progress
In peer-to-peer (P2P) social lending, it is important to predict the repayment of borrowers. P2P lending data are generated in real-time, but most of them are pending to decide the repayment because the deadline is not yet expired. Adding the unexpir...

Lexicase Selection for Multi-Task Evolutionary Robotics.

Artificial life
In Evolutionary Robotics, Lexicase selection has proven effective when a single task is broken down into many individual parameterizations. Evolved individuals have generalized across unique configurations of an overarching task. Here, we investigate...

Using the Comparative Hybrid Approach to Disentangle the Role of Substrate Choice on the Evolution of Cognition.

Artificial life
Understanding the structure and evolution of natural cognition is a topic of broad scientific interest, as is the development of an engineering toolkit to construct artificial cognitive systems. One open question is determining which components and t...

Convolutional neural network-based artificial intelligence for the diagnosis of early esophageal cancer based on endoscopic images: A meta-analysis.

Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association
BACKGROUND: Early screening and treatment of esophageal cancer (EC) is particularly important for the survival and prognosis of patients. However, early EC is difficult to diagnose by a routine endoscopic examination. Therefore, convolutional neural ...

Estimation of patient's angle from skull radiographs using deep learning.

Journal of X-ray science and technology
BACKGROUND: Skull radiography, an assessment method for initial diagnosis and post-operative follow-up, requires substantial retaking of various types of radiographs. During retaking, a radiologic technologist estimates a patient's rotation angle fro...