AIMC Topic: Algorithms

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Two-phase non-invasive multi-disease detection via sublingual region.

Computers in biology and medicine
Non-invasive multi-disease detection is an active technology that detects human diseases automatically. By observing images of the human body, computers can make inferences on disease detection based on artificial intelligence and computer vision tec...

Generation of the NIR Spectral Band for Satellite Images with Convolutional Neural Networks.

Sensors (Basel, Switzerland)
The near-infrared (NIR) spectral range (from 780 to 2500 nm) of the multispectral remote sensing imagery provides vital information for landcover classification, especially concerning vegetation assessment. Despite the usefulness of NIR, it does not ...

A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images.

Computational intelligence and neuroscience
The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large group of viruses that can infect animals and humans and cause respiratory distress; these discomforts may be as mild as a cold or as severe as pneumonia....

Reliable impulsive synchronization for fuzzy neural networks with mixed controllers.

Neural networks : the official journal of the International Neural Network Society
This work studies the synchronization of the master-slave (MS) fuzzy neural networks (FNNs) with random actuator failure, where the state information of the master FNNs can not be obtained directly. To reduce the loads of the communication channel an...

Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram.

The Canadian journal of cardiology
BACKGROUND: Current electrocardiogram analysis algorithms cannot predict the presence of coronary artery disease (CAD), especially in stable patients. This study assessed the ability of an artificial intelligence algorithm (ECGio; HEARTio Inc, Pittsb...

Machine Learning Approach to Analyze the Surface Properties of Biological Materials.

ACS biomaterials science & engineering
Similar to how CRISPR has revolutionized the field of molecular biology, machine learning may drastically boost research in the area of materials science. Machine learning is a fast-evolving method that allows for analyzing big data and unveiling cor...

Diagnosis of Wilson Disease and Its Phenotypes by Using Artificial Intelligence.

Biomolecules
WD is caused by variants disrupting copper efflux resulting in excessive copper accumulation mainly in liver and brain. The diagnosis of WD is challenged by its variable clinical course, onset, morbidity, and variant type. Currently it is diagnosed...

Fault-tolerant scheme for robotic manipulator-Nonlinear robust back-stepping control with friction compensation.

PloS one
Emerging applications of autonomous robots requiring stability and reliability cannot afford component failure to achieve operational objectives. Hence, identification and countermeasure of a fault is of utmost importance in mechatronics community. T...

Extremely randomized neural networks for constructing prediction intervals.

Neural networks : the official journal of the International Neural Network Society
The aim of this paper is to propose a novel prediction model based on an ensemble of deep neural networks adapting the extremely randomized trees method originally developed for random forests. The extra-randomness introduced in the ensemble reduces ...

Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Biological neurons have adaptive nature and perform complex computations involving the filtering of redundant information. However, most common neural cell models, including biologically plausible, such as Hodgkin-Huxley or Izhikevich, do not possess...