AI Medical Compendium Topic

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

Principal Component Analysis

Showing 161 to 170 of 606 articles

Clear Filters

A hybrid EEG classification model using layered cascade deep learning architecture.

Medical & biological engineering & computing
The problem of multi-class classification is always a challenge in the field of EEG (electroencephalogram)-based seizure detection. The traditional studies focus on computing or learning a set of features from EEG to distinguish between different pat...

Descriptor generation from Morgan fingerprint using persistent homology.

SAR and QSAR in environmental research
In cheminformatics, molecular fingerprints (FPs) are used in various tasks such as regression and classification. However, predictive models often underutilize Morgan FP for regression and related tasks in machine learning. This study introduced desc...

Guided principal component analysis (GPCA): a simple method for improving detection of a known analyte.

The Analyst
There is increasing interest in the application of Raman spectroscopy in a medical setting, ranging from supporting real-time clinical decisions surgical margins to assisting pathologists with disease classification. However, there remain a number o...

Variable selection for nonlinear dimensionality reduction of biological datasets through bootstrapping of correlation networks.

Computers in biology and medicine
Identifying the most relevant variables or features in massive datasets for dimensionality reduction can lead to improved and more informative display, faster computation times, and more explainable models of complex systems. Despite significant adva...

Clustering Methods for Vibro-Acoustic Sensing Features as a Potential Approach to Tissue Characterisation in Robot-Assisted Interventions.

Sensors (Basel, Switzerland)
This article provides a comprehensive analysis of the feature extraction methods applied to vibro-acoustic signals (VA signals) in the context of robot-assisted interventions. The primary objective is to extract valuable information from these signal...

A quality detection method of corn based on spectral technology and deep learning model.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Corn is an important food crop in the world. With economic development and population growth, the nutritional quality of corn is of great significance to high-quality breeding, scientific cultivation and fine management. Aiming at the problems of cum...

Sparse discriminant PCA based on contrastive learning and class-specificity distribution.

Neural networks : the official journal of the International Neural Network Society
Much mathematical effort has been devoted to developing Principal Component Analysis (PCA), which is the most popular feature extraction method. To suppress the negative effect of noise on PCA performance, there have been extensive studies and applic...

Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy.

Scientific reports
This investigation aimed to assess the effectiveness of different classification models in diagnosing prostate cancer using a screening dataset obtained from the National Cancer Institute's Cancer Data Access System. The dataset was first reduced usi...

Fragments quantum descriptors in classification of bio-accumulative compounds.

Journal of molecular graphics & modelling
The aim of the following research is to assess the applicability of calculated quantum properties of molecular fragments as molecular descriptors in machine learning classification task. The research is based on bio-concentration and QM9-extended dat...

Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model.

Sensors (Basel, Switzerland)
Machining is a crucial constituent of the manufacturing industry, which has begun to transition from precision machinery to smart machinery. Particularly, the introduction of artificial intelligence into computer numerically controlled (CNC) machine ...