AIMC Topic: Algorithms

Clear Filters Showing 12341 to 12350 of 28713 articles

Dimensionality reduction of longitudinal 'omics data using modern tensor factorizations.

PLoS computational biology
Longitudinal 'omics analytical methods are extensively used in the evolving field of precision medicine, by enabling 'big data' recording and high-resolution interpretation of complex datasets, driven by individual variations in response to perturbat...

Transfer Learning-Based Condition Monitoring of Single Point Cutting Tool.

Computational intelligence and neuroscience
Machining activities in recent times have shifted their focus towards tool life and tool wear. Cutting tools have been utilized on a daily basis and play a vital role in manufacturing industries. Prolonged and incessant operation of the cutting tool ...

A Machine Learning and Deep Learning Approach for Recognizing Handwritten Digits.

Computational intelligence and neuroscience
Optical character recognition (OCR) can be a subcategory of graphic design that involves extracting text from images or scanned documents. We have chosen to make unique handwritten digits available on the Modified National Institute of Standards and ...

A powerful tool for near-infrared spectroscopy: Synergy adaptive moving window algorithm based on the immune support vector machine.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Traditional trial-and-error methods are time-consuming and inefficient, especially very unfriendly to inexperienced analysts, and are sometimes still used to select preprocessing methods or wavelength variables in near-infrared spectroscopy (NIR). To...

Development and external validation of predictive algorithms for six-week mortality in spinal metastasis using 4,304 patients from five institutions.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: Historically, spine surgeons used expected postoperative survival of 3-months to help select candidates for operative intervention in spinal metastasis. However, this cutoff has been challenged by the development of minimally inva...

A multi-birth metric learning framework based on binary constraints.

Neural networks : the official journal of the International Neural Network Society
Multi-metric learning plays a significant role in improving the generalization of algorithms related to distance metrics since using a single metric is sometimes insufficient to handle complex data. Metric learning can adjust automatically the distan...

An ensemble framework for microarray data classification based on feature subspace partitioning.

Computers in biology and medicine
Feature selection is exposed to the curse of dimensionality risk, and it is even more exacerbated with high-dimensional data such as microarrays. Moreover, the low-instance/high-feature (LIHF) property of microarray data needs considerable processing...

A novel machine learning model based on sparse structure learning with adaptive graph regularization for predicting drug side effects.

Journal of biomedical informatics
Drug side effects are closely related to the success and failure of drug development. Here we present a novel machine learning method for side effect prediction. The proposed method treats side effect prediction as a multi-label learning problem and ...

A Novel Memory and Time-Efficient ALPR System Based on YOLOv5.

Sensors (Basel, Switzerland)
With the rapid development of deep learning techniques, new innovative license plate recognition systems have gained considerable attention from researchers all over the world. These systems have numerous applications, such as law enforcement, parkin...

Panoramic Manifold Projection (Panoramap) for Single-Cell Data Dimensionality Reduction and Visualization.

International journal of molecular sciences
Nonlinear dimensionality reduction (NLDR) methods such as t-Distributed Stochastic Neighbour Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) have been widely used for biological data exploration, especially in single-cell a...