AIMC Topic: Models, Theoretical

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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...

A neural controller for online laser power adjustment during the heat therapy process in the presence of nanoparticles.

Australasian physical & engineering sciences in medicine
The present research evaluated the efficiency of a control approach to control the temperature of a breast tumor mass in the presence of nanoparticles exposed to laser radiation. However, if the radiation is carried out in open loop manner it may res...

Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning.

Evolutionary computation
This article tackles the Distribution Network Expansion Planning (DNEP) problem that has to be solved by distribution network operators to decide which, where, and/or when enhancements to electricity networks should be introduced to satisfy the futur...

Comparative study of ANN and RSM for simultaneous optimization of multiple targets in Fenton treatment of landfill leachate.

Waste management (New York, N.Y.)
In this study, two modeling methods, namely response surface methodology (RSM) and artificial neural networks (ANN), were applied to investigate the Fenton process performance in landfill leachate treatment. For this purpose, three targets were used ...

Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

Physics in medicine and biology
A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated ...

Relevance popularity: A term event model based feature selection scheme for text classification.

PloS one
Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the numbe...

Towards autonomous locomotion: CPG-based control of smooth 3D slithering gait transition of a snake-like robot.

Bioinspiration & biomimetics
Snake-like robots with 3D locomotion ability have significant advantages of adaptive travelling in diverse complex terrain over traditional legged or wheeled mobile robots. Despite numerous developed gaits, these snake-like robots suffer from unsmoot...

A neural joint model for entity and relation extraction from biomedical text.

BMC bioinformatics
BACKGROUND: Extracting biomedical entities and their relations from text has important applications on biomedical research. Previous work primarily utilized feature-based pipeline models to process this task. Many efforts need to be made on feature e...