AIMC Topic: Models, Theoretical

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An inexact multistage fuzzy-stochastic programming for regional electric power system management constrained by environmental quality.

Environmental science and pollution research international
Electric power system involves different fields and disciplines which addressed the economic system, energy system, and environment system. Inner uncertainty of this compound system would be an inevitable problem. Therefore, an inexact multistage fuz...

Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...

Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.

Journal of biomedical semantics
BACKGROUND: Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies s...

A machine learning approach for predicting methionine oxidation sites.

BMC bioinformatics
BACKGROUND: The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regulatory post-translational modi...

Fuzzy-Rough Cognitive Networks.

Neural networks : the official journal of the International Neural Network Society
Rough Cognitive Networks (RCNs) are a kind of granular neural network that augments the reasoning rule present in Fuzzy Cognitive Maps with crisp information granules coming from Rough Set Theory. While RCNs have shown promise in solving different cl...

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation.

Environmental pollution (Barking, Essex : 1987)
Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutants. However, existing methods of air pollutant concentration prediction fail to effectively model lon...

Risk Prediction for Portal Vein Thrombosis in Acute Pancreatitis Using Radial Basis Function.

Annals of vascular surgery
BACKGROUND: Acute pancreatitis (AP) can induce portosplenomesenteric vein thrombosis (PVT), which may generate higher morbidity and mortality. However current diagnostic modalities for PVT are still controversial. In recent decades, artificial neural...

Probing the toxicity of nanoparticles: a unified in silico machine learning model based on perturbation theory.

Nanotoxicology
Nanoparticles (NPs) are part of our daily life, having a wide range of applications in engineering, physics, chemistry, and biomedicine. However, there are serious concerns regarding the harmful effects that NPs can cause to the different biological ...

A spatio-temporal prediction model based on support vector machine regression: Ambient Black Carbon in three New England States.

Environmental research
Fine ambient particulate matter has been widely associated with multiple health effects. Mitigation hinges on understanding which sources are contributing to its toxicity. Black Carbon (BC), an indicator of particles generated from traffic sources, h...

A deep learning-based multi-model ensemble method for cancer prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged i...