AIMC Topic: Neural Networks, Computer

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Multi-level feature aggregation network for instrument identification of endoscopic images.

Physics in medicine and biology
Identification of surgical instruments is crucial in understanding surgical scenarios and providing an assistive process in endoscopic image-guided surgery. This study proposes a novel multilevel feature-aggregated deep convolutional neural network (...

Comparison of Convolutional Neural Network Models for Determination of Vocal Fold Normality in Laryngoscopic Images.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Deep learning using convolutional neural networks (CNNs) is widely used in medical imaging research. This study was performed to investigate if vocal fold normality in laryngoscopic images can be determined by CNN-based deep learning and ...

iPiDA-sHN: Identification of Piwi-interacting RNA-disease associations by selecting high quality negative samples.

Computational biology and chemistry
As a large group of small non-coding RNAs (ncRNAs), Piwi-interacting RNAs (piRNAs) have been detected to be associated with various diseases. Identifying disease associated piRNAs can provide promising candidate molecular targets to promote the drug ...

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Detection and characterization of focal liver lesions (FLLs) is key for optimizing treatment for patients who may have a primary hepatic cancer or metastatic disease to the liver. This is the first study to develop an EUS-based c...

Unsupervised spectral mapping and feature selection for hyperspectral anomaly detection.

Neural networks : the official journal of the International Neural Network Society
Exploring techniques that breakthrough the unknown space or material species is of considerable significance to military and civilian fields, and it is a challenging task without any prior information. Nowadays, the use of material-specific spectral ...

Human thermal sensation over a mountainous area, revealed by the application of ANNs: the case of Ainos Mt., Kefalonia Island, Greece.

International journal of biometeorology
Mt. Ainos in Kefalonia Island, Greece, hosts a large variety of plant species, some of them endemic to the region. Because of its rich biodiversity, a large portion of the mountain area is designated as National Park and is protected from human activ...

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning.

European journal of radiology
PURPOSE: During the emerging COVID-19 pandemic, radiology departments faced a substantial increase in chest CT admissions coupled with the novel demand for quantification of pulmonary opacities. This article describes how our clinic implemented an au...

Fully-Connected Neural Networks with Reduced Parameterization for Predicting Histological Types of Lung Cancer from Somatic Mutations.

Biomolecules
Several challenges appear in the application of deep learning to genomic data. First, the dimensionality of input can be orders of magnitude greater than the number of samples, forcing the model to be prone to overfitting the training dataset. Second...

PASCAL: a pseudo cascade learning framework for breast cancer treatment entity normalization in Chinese clinical text.

BMC medical informatics and decision making
BACKGROUNDS: Knowledge discovery from breast cancer treatment records has promoted downstream clinical studies such as careflow mining and therapy analysis. However, the clinical treatment text from electronic health data might be recorded by differe...

Instance Transfer Subject-Dependent Strategy for Motor Imagery Signal Classification Using Deep Convolutional Neural Networks.

Computational and mathematical methods in medicine
In the process of brain-computer interface (BCI), variations across sessions/subjects result in differences in the properties of potential of the brain. This issue may lead to variations in feature distribution of electroencephalogram (EEG) across su...