AIMC Topic: Algorithms

Clear Filters Showing 21741 to 21750 of 28713 articles

Improving deep convolutional neural networks with mixed maxout units.

PloS one
Motivated by insights from the maxout-units-based deep Convolutional Neural Network (CNN) that "non-maximal features are unable to deliver" and "feature mapping subspace pooling is insufficient," we present a novel mixed variant of the recently intro...

A computationally efficient method for hand-eye calibration.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical robots with cooperative control and semiautonomous features have shown increasing clinical potential, particularly for repetitive tasks under imaging and vision guidance. Effective performance of an autonomous task requires accurate...

Multi-modal discriminative dictionary learning for Alzheimer's disease and mild cognitive impairment.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The differentiation of mild cognitive impairment (MCI), which is the prodromal stage of Alzheimer's disease (AD), from normal control (NC) is important as the recent research emphasis on early pre-clinical stage for possible...

pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.

Gene
Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computationa...

Knowledge-transfer learning for prediction of matrix metalloprotease substrate-cleavage sites.

Scientific reports
Matrix Metalloproteases (MMPs) are an important family of proteases that play crucial roles in key cellular and disease processes. Therefore, MMPs constitute important targets for drug design, development and delivery. Advanced proteomic technologies...

EEG machine learning for accurate detection of cholinergic intervention and Alzheimer's disease.

Scientific reports
Monitoring effects of disease or therapeutic intervention on brain function is increasingly important for clinical trials, albeit hampered by inter-individual variability and subtle effects. Here, we apply complementary biomarker algorithms to electr...

A neural network approach for fast, automated quantification of DIR performance.

Medical physics
PURPOSE: A critical step in adaptive radiotherapy (ART) workflow is deformably registering the simulation CT with the daily or weekly volumetric imaging. Quantifying the deformable image registration accuracy under these circumstances is a complex ta...

Classification of Diffusion Tensor Metrics for the Diagnosis of a Myelopathic Cord Using Machine Learning.

International journal of neural systems
In this study, we propose an automated framework that combines diffusion tensor imaging (DTI) metrics with machine learning algorithms to accurately classify control groups and groups with cervical spondylotic myelopathy (CSM) in the spinal cord. The...

Design and Implementation of a Smart Home System Using Multisensor Data Fusion Technology.

Sensors (Basel, Switzerland)
This paper aims to develop a multisensor data fusion technology-based smart home system by integrating wearable intelligent technology, artificial intelligence, and sensor fusion technology. We have developed the following three systems to create an ...

An Automatic Detection System of Lung Nodule Based on Multigroup Patch-Based Deep Learning Network.

IEEE journal of biomedical and health informatics
High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung cancer. It is a significant and challenging task to quickly locate the exact positions of lung nodules. Extensive work has been done by researchers around t...