AI Medical Compendium Topic

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

Principal Component Analysis

Showing 581 to 590 of 607 articles

Clear Filters

Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.

Methods in molecular biology (Clifton, N.J.)
The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, identifying the most biologically coherent set of biomarkers can be a particularly daunting step. In...

Augmenting intracortical brain-machine interface with neurally driven error detectors.

Journal of neural engineering
OBJECTIVE: Making mistakes is inevitable, but identifying them allows us to correct or adapt our behavior to improve future performance. Current brain-machine interfaces (BMIs) make errors that need to be explicitly corrected by the user, thereby con...

Intravoxel Incoherent Motion: Model-Free Determination of Tissue Type in Abdominal Organs Using Machine Learning.

Investigative radiology
PURPOSE: For diffusion data sets including low and high b-values, the intravoxel incoherent motion model is commonly applied to characterize tissue. The aim of the present study was to show that machine learning allows a model-free approach to determ...

Evaluating the use of neural networks and acoustic measurements to identify laryngeal pathologies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nineteen acoustical measurements were related to 23 larynx conditions by artificial neural networks (ANNs) and principal component analysis. An exhaustive analysis (combining all possible sets of acoustical measurements as ANN inputs) showed a perfor...

Qualitative analysis of biological tuberculosis samples by an electronic nose-based artificial neural network.

The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
OBJECTIVE: To apply an e-nose system for monitoring headspace volatiles in biological samples from Egyptian patients with active pulmonary tuberculosis (TB) and healthy controls (HCs) and compare them with standard sputum analysis.

Epileptic seizure detection in EEG signal with GModPCA and support vector machine.

Bio-medical materials and engineering
BACKGROUND AND OBJECTIVE: Epilepsy is one of the most common neurological disorders caused by recurrent seizures. Electroencephalograms (EEGs) record neural activity and can detect epilepsy. Visual inspection of an EEG signal for epileptic seizure de...

Identification of self-interacting proteins by exploring evolutionary information embedded in PSI-BLAST-constructed position specific scoring matrix.

Oncotarget
Self-interacting Proteins (SIPs) play an essential role in a wide range of biological processes, such as gene expression regulation, signal transduction, enzyme activation and immune response. Because of the limitations for experimental self-interact...

Principal component analysis can decrease neural networks performance for incipient falls detection: A preliminary study with hands and feet accelerations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fall-related accidents constitute a major problem for elderly people and a burden to the health-care national system. It is therefore important to design devices (e.g., accelerometers) and machine learning algorithms able to recognize incipient falls...

Classification of EEG based-mental fatigue using principal component analysis and Bayesian neural network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper presents an electroencephalography (EEG) based-classification of between pre- and post-mental load tasks for mental fatigue detection from 65 healthy participants. During the data collection, eye closed and eye open tasks were collected be...