AI Medical Compendium Topic:
Models, Theoretical

Clear Filters Showing 1101 to 1110 of 1795 articles

Distributed optimization of multi-class SVMs.

PloS one
Training of one-vs.-rest SVMs can be parallelized over the number of classes in a straight forward way. Given enough computational resources, one-vs.-rest SVMs can thus be trained on data involving a large number of classes. The same cannot be stated...

Transition index maps for urban growth simulation: application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation.

Environmental monitoring and assessment
Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) mode...

Predicting Zoonotic Risk of Influenza A Viruses from Host Tropism Protein Signature Using Random Forest.

International journal of molecular sciences
Influenza A viruses remain a significant health problem, especially when a novel subtype emerges from the avian population to cause severe outbreaks in humans. Zoonotic viruses arise from the animal population as a result of mutations and reassortmen...

Classification of Paediatric Inflammatory Bowel Disease using Machine Learning.

Scientific reports
Paediatric inflammatory bowel disease (PIBD), comprising Crohn's disease (CD), ulcerative colitis (UC) and inflammatory bowel disease unclassified (IBDU) is a complex and multifactorial condition with increasing incidence. An accurate diagnosis of PI...

Predicting and understanding law-making with word vectors and an ensemble model.

PloS one
Out of nearly 70,000 bills introduced in the U.S. Congress from 2001 to 2015, only 2,513 were enacted. We developed a machine learning approach to forecasting the probability that any bill will become law. Starting in 2001 with the 107th Congress, we...

A time series driven decomposed evolutionary optimization approach for reconstructing large-scale gene regulatory networks based on fuzzy cognitive maps.

BMC bioinformatics
BACKGROUND: Reconstructing gene regulatory networks (GRNs) from expression data plays an important role in understanding the fundamental cellular processes and revealing the underlying relations among genes. Although many algorithms have been propose...

Prediction of the severity of obstructive sleep apnea by anthropometric features via support vector machine.

PloS one
To develop an applicable prediction for obstructive sleep apnea (OSA) is still a challenge in clinical practice. We apply a modern machine learning method, the support vector machine to establish a predicting model for the severity of OSA. The suppor...

In Silico Prediction of Chemicals Binding to Aromatase with Machine Learning Methods.

Chemical research in toxicology
Environmental chemicals may affect endocrine systems through multiple mechanisms, one of which is via effects on aromatase (also known as CYP19A1), an enzyme critical for maintaining the normal balance of estrogens and androgens in the body. Therefor...

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

American journal of public health
OBJECTIVES: To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services.

The way to cover prediction for cytotoxicity for all existing nano-sized metal oxides by using neural network method.

Nanotoxicology
The regulatory agencies should fulfil the data gap in toxicity for new chemicals including nano-sized compounds, like metal oxides nanoparticles (MeO NPs) according to the registration, evaluation, authorisation and restriction of chemicals (REACH) l...