AIMC Topic: Male

Clear Filters Showing 19831 to 19840 of 27433 articles

A Deep Learning Algorithm for Prediction of Age-Related Eye Disease Study Severity Scale for Age-Related Macular Degeneration from Color Fundus Photography.

Ophthalmology
PURPOSE: Age-related macular degeneration (AMD) is a common threat to vision. While classification of disease stages is critical to understanding disease risk and progression, several systems based on color fundus photographs are known. Most of these...

Coronary CT Angiography-derived Fractional Flow Reserve: Machine Learning Algorithm versus Computational Fluid Dynamics Modeling.

Radiology
Purpose To compare two technical approaches for determination of coronary computed tomography (CT) angiography-derived fractional flow reserve (FFR)-FFR derived from coronary CT angiography based on computational fluid dynamics (hereafter, FFR) and F...

Automated detection of focal cortical dysplasia type II with surface-based magnetic resonance imaging postprocessing and machine learning.

Epilepsia
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) postprocessing methods may provide essential help for detection of FCD. In ...

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

Journal of medical systems
Diabetes mellitus is a group of metabolic diseases in which blood sugar levels are too high. About 8.8% of the world was diabetic in 2017. It is projected that this will reach nearly 10% by 2045. The major challenge is that when machine learning-base...

An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

BMC nephrology
BACKGROUND: Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for cli...

Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy.

BMC psychiatry
BACKGROUND: Early diagnosis of schizophrenia could improve the outcome of the illness. Unlike classical between-group comparisons, machine learning can identify subtle disease patterns on a single subject level, which could help realize the potential...

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PLoS computational biology
Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN frame...

Psychosocial factors associated with intended use of automated vehicles: A simulated driving study.

Accident; analysis and prevention
This study applied the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to assess drivers' intended use of automated vehicles (AVs) after undertaking a simulated driving task. In addition, this study explored the potential f...

Creation of knowledge-based planning models intended for large scale distribution: Minimizing the effect of outlier plans.

Journal of applied clinical medical physics
Knowledge-based planning (KBP) can be used to estimate dose-volume histograms (DVHs) of organs at risk (OAR) using models. The task of model creation, however, can result in estimates with differing accuracy; particularly when outlier plans are not p...