AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Linear Models

Showing 261 to 270 of 559 articles

Clear Filters

Artificial neural network metamodel for sensitivity analysis in a total hip replacement health economic model.

Expert review of pharmacoeconomics & outcomes research
: Metamodels have been used to approximate complex simulations and have many applications with sensitivity analysis, optimization, etc. However, their use in health economics is very limited. Application of artificial neural network (ANN) with a heal...

Automatic monitoring system for individual dairy cows based on a deep learning framework that provides identification via body parts and estimation of body condition score.

Journal of dairy science
Body condition score (BCS) is a common tool for indirectly estimating the mobilization of energy reserves in the fat and muscle of cattle that meets the requirements of animal welfare and precision livestock farming for the effective monitoring of in...

Prediction of environmental effects in received signal strength in FM/TV station based on meteorological parameters using artificial neural network and data mining.

Journal of environmental management
In this paper, meteorological parameters, electric field strength and transmitters' output power measured during six months in a TV/FM station. There are 13 frequencies in FM and UHF frequency bands in pilot broadcast station. The analysis of results...

Predicting the acute ecotoxicity of chemical substances by machine learning using graph theory.

Chemosphere
Accurate in silico predictions of chemical substance ecotoxicity has become an important issue in recent years. Most conventional methods, such as the Ecological Structure-Activity Relationship (ECOSAR) model, cluster chemical substances empirically ...

Using artificial neural networks to predict pH, ammonia, and volatile fatty acid concentrations in the rumen.

Journal of dairy science
The objectives of this study were (1) to predict ruminal pH and ruminal ammonia and volatile fatty acid (VFA) concentrations by developing artificial neural networks (ANN) using dietary nutrient compositions, dry matter intake, and body weight as inp...

Mapping urban air quality using mobile sampling with low-cost sensors and machine learning in Seoul, South Korea.

Environment international
Recent studies have demonstrated that mobile sampling can improve the spatial granularity of land use regression (LUR) models. Mobile sampling campaigns deploying low-cost (<$300) air quality sensors could potentially offer an inexpensive and practic...

Spread of α-synuclein pathology through the brain connectome is modulated by selective vulnerability and predicted by network analysis.

Nature neuroscience
Studies of patients afflicted by neurodegenerative diseases suggest that misfolded proteins spread through the brain along anatomically connected networks, prompting progressive decline. Recently, mouse models have recapitulated the cell-to-cell tran...

Assessment of lipid peroxidation and artificial neural network models in early Alzheimer Disease diagnosis.

Clinical biochemistry
OBJECTIVE: Lipid peroxidation constitutes a molecular mechanism involved in early Alzheimer Disease (AD) stages, and artificial neural network (ANN) analysis is a promising non-linear regression model, characterized by its high flexibility and utilit...

Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration.

Journal of the American College of Surgeons
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and earlier models include data not available at the time of scheduling. Our objective was to develop stat...