In this study, two novel fuzzy decision approaches, where the fuzzy logic (FL) model was revised with the C4.5 decision tree (DT) algorithm, were applied to the classification of cyclist injury-severity in bicycle-vehicle accidents. The study aims to...
This paper focus on a neural network classification model to estimate the association among gender, race, BMI, age, smoking, kidney disease and diabetes in hypertensive patients. It also shows that artificial neural network techniques applied to larg...
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Providing prognostic information at the time of cancer diagnosis has important implications for treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and clinical variables can provide useful prognostic ...
Proceedings of the National Academy of Sciences of the United States of America
May 26, 2020
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening are being adopted worldwide by medical institutions. In such a context, generating fair and unbiased classifiers becomes of paramount importance. The research...
OBJECTIVE: To apply unsupervised machine learning to patient-reported outcomes to identify clusters of epilepsy patients exhibiting unique psychosocial characteristics.
BACKGROUND: Preoperative prognostication of adverse events (AEs) for patients undergoing surgery for lumbar degenerative spondylolisthesis (LDS) can improve risk stratification and help guide the surgical decision-making process. The aim of this stud...
BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adverse events. This research examines the efficacy of using artificial neural networks (ANNs) to predict...
Geriatrics & gerontology international
Feb 19, 2020
AIM: The primary aim of this study was to examine the impact of age, gender and the stage of dementia on the results of an assistive technology intervention that make use of communication robots (com-robots). The intervention was designed to improve ...
BACKGROUND: Deep learning has always been at the forefront of scientific research. It has also been applied to medical research. Hereditary spinocerebellar ataxia (SCA) is characterized by gait abnormalities and is usually evaluated semi-quantitative...