AIMC Topic: Machine Learning

Clear Filters Showing 23651 to 23660 of 34417 articles

Categorization of free-text drug orders using character-level recurrent neural networks.

International journal of medical informatics
BACKGROUND AND PURPOSE: Manual annotation and categorization of non-standardized text ("free-text") of drug orders entered into electronic health records is a labor-intensive task. However, standardization is required for drug order analyses and has ...

Approximate neural optimal control with reinforcement learning for a torsional pendulum device.

Neural networks : the official journal of the International Neural Network Society
A torsional pendulum device containing hyperbolic tangent input nonlinearities can be formulated as a nonaffine system. Unlike basic affine systems, the optimal feedback control of complex nonaffine plants is difficult but quite important. In this pa...

Machine Learning Prediction of Liver Stiffness Using Clinical and T2-Weighted MRI Radiomic Data.

AJR. American journal of roentgenology
The purpose of this study is to develop a machine learning model to categorically classify MR elastography (MRE)-derived liver stiffness using clinical and nonelastographic MRI radiomic features in pediatric and young adult patients with known or su...

DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information.

Journal of computer-aided molecular design
DNA-binding proteins (DBPs) participate in various biological processes including DNA replication, recombination, and repair. In the human genome, about 6-7% of these proteins are utilized for genes encoding. DBPs shape the DNA into a compact structu...

Effect of Depth and Width on Local Minima in Deep Learning.

Neural computation
In this paper, we analyze the effects of depth and width on the quality of local minima, without strong overparameterization and simplification assumptions in the literature. Without any simplification assumption, for deep nonlinear neural networks w...

Gene shaving using a sensitivity analysis of kernel based machine learning approach, with applications to cancer data.

PloS one
BACKGROUND: Gene shaving (GS) is an essential and challenging tools for biomedical researchers due to the large number of genes in human genome and the complex nature of biological networks. Most GS methods are not applicable to non-linear and multi-...

Breast cancer outcome prediction with tumour tissue images and machine learning.

Breast cancer research and treatment
PURPOSE: Recent advances in machine learning have enabled better understanding of large and complex visual data. Here, we aim to investigate patient outcome prediction with a machine learning method using only an image of tumour sample as an input.

Intuition-Enabled Machine Learning Beats the Competition When Joint Human-Robot Teams Perform Inorganic Chemical Experiments.

Journal of chemical information and modeling
Traditionally, chemists have relied on years of training and accumulated experience in order to discover new molecules. But the space of possible molecules is so vast that only a limited exploration with the traditional methods can be ever possible. ...