AIMC Topic: Machine Learning

Clear Filters Showing 23331 to 23340 of 34417 articles

Artificial intelligence for assisting diagnostics and assessment of Parkinson's disease-A review.

Clinical neurology and neurosurgery
Artificial intelligence, specifically machine learning, has found numerous applications in computer-aided diagnostics, monitoring and management of neurodegenerative movement disorders of parkinsonian type. These tasks are not trivial due to high int...

Robust outcome weighted learning for optimal individualized treatment rules.

Journal of biopharmaceutical statistics
Personalized medicine has received increasing attentions among scientific communities in recent years. Because patients often have heterogenous responses to treatments, discovering individualized treatment rules (ITR) is an important component of pre...

Prediction of ATP-binding sites in membrane proteins using a two-dimensional convolutional neural network.

Journal of molecular graphics & modelling
Membrane proteins, the most important drug targets, account for around 30% of total proteins encoded by the genome of living organisms. An important role of these proteins is to bind adenosine triphosphate (ATP), facilitating crucial biological proce...

Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.

Statistics in medicine
Feature selection is an important initial step of exploratory analysis in biomedical studies. Its main objective is to eliminate the covariates that are uncorrelated with the outcome. For highly correlated covariates, traditional feature selection me...

Delay-dependent criterion for asymptotic stability of a class of fractional-order memristive neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
The Lyapunov-Krasovskii functional approach is an important and effective delay-dependent stability analysis method for integer order system. However, it cannot be applied directly to fractional-order (FO) systems. To obtain delay-dependent stability...

Recurrent transform learning.

Neural networks : the official journal of the International Neural Network Society
Recurrent neural networks (RNN) model time series by feeding back the representation from the previous time instant as an input for the current instant along with exogenous inputs. Two main shortcomings of RNN are - 1. The problem of vanishing gradie...

Computational Systems Pharmacology-Target Mapping for Fentanyl-Laced Cocaine Overdose.

ACS chemical neuroscience
The United States of America is fighting against one of its worst-ever drug crises. Over 900 people a week die from opioid- or heroin-related overdoses, while millions more suffer from opioid prescription addiction. Recently, drug overdoses caused by...

Machine-learning-guided directed evolution for protein engineering.

Nature methods
Protein engineering through machine-learning-guided directed evolution enables the optimization of protein functions. Machine-learning approaches predict how sequence maps to function in a data-driven manner without requiring a detailed model of the ...