AIMC Topic: Neural Networks, Computer

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Machine Learning Classification of One-Chiral-Center Organic Molecules According to Optical Rotation.

Journal of chemical information and modeling
In this study, machine learning algorithms were investigated for the classification of organic molecules with one carbon chiral center according to the sign of optical rotation. Diverse heterogeneous data sets comprising up to 13,080 compounds and th...

Almost Periodicity in Impulsive Fractional-Order Reaction-Diffusion Neural Networks With Time-Varying Delays.

IEEE transactions on cybernetics
A neural-network model of fractional order with impulsive perturbations, time-varying delays, and reaction-diffusion terms is investigated in this article. The focus is on investigating qualitative properties of the states and developing new almost p...

Fused Sparse Network Learning for Longitudinal Analysis of Mild Cognitive Impairment.

IEEE transactions on cybernetics
Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and progressive process. To understand the brain functions and identify the biomarkers of AD and early stages of the disease [also known as, mild cognitive impairment (MCI)]...

Segmentation and classification of thyroid follicular neoplasm using cascaded convolutional neural network.

Physics in medicine and biology
In this paper, we present a segmentation and classification method for thyroid follicular neoplasms based on a combination of the prior-based level set method and deep convolutional neural network. The proposed method aims to discriminate thyroid fol...

Inter-floor noise classification using convolutional neural network.

PloS one
In apartment houses, noise between floors can disturb pleasant living environments and cause disputes between neighbors. As a means of resolving disputes caused by inter-floor noise, noises are recorded for 24 hours in a household to verify whether t...

DeepCLA: A Hybrid Deep Learning Approach for the Identification of Clathrin.

Journal of chemical information and modeling
Clathrin is a highly evolutionarily conserved protein, which can affect membrane cleavage and membrane release of vesicles. The absence of clathrin in the cellular system affects a variety of human diseases. Effective recognition of clathrin plays an...

Explainable Deep Relational Networks for Predicting Compound-Protein Affinities and Contacts.

Journal of chemical information and modeling
Predicting compound-protein affinity is beneficial for accelerating drug discovery. Doing so without the often-unavailable structure data is gaining interest. However, recent progress in structure-free affinity prediction, made by machine learning, f...

Utilizing an Artificial Neural Network to Predict Self-Management in Patients With Chronic Obstructive Pulmonary Disease: An Exploratory Analysis.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: The main objective of this study was to utilize an artificial neural network in an exploratory fashion to predict self-management behaviors based on reported symptoms in a sample of stable patients with chronic obstructive pulmonary disease ...

Saak Transform-Based Machine Learning for Light-Sheet Imaging of Cardiac Trabeculation.

IEEE transactions on bio-medical engineering
OBJECTIVE: Recent advances in light-sheet fluorescence microscopy (LSFM) enable 3-dimensional (3-D) imaging of cardiac architecture and mechanics in toto. However, segmentation of the cardiac trabecular network to quantify cardiac injury remains a ch...

An IoT and Fog Computing-Based Monitoring System for Cardiovascular Patients with Automatic ECG Classification Using Deep Neural Networks.

Sensors (Basel, Switzerland)
Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The s...