AIMC Topic: Deep Learning

Clear Filters Showing 15261 to 15270 of 28423 articles

DeepBtoD: Improved RNA-binding proteins prediction via integrated deep learning.

Journal of bioinformatics and computational biology
RNA-binding proteins (RBPs) have crucial roles in various cellular processes such as alternative splicing and gene regulation. Therefore, the analysis and identification of RBPs is an essential issue. However, although many computational methods have...

A hybrid deep learning approach for driver anomalous lane changing identification.

Accident; analysis and prevention
Reliable knowledge of driving states is of great importance to ensure road safety. Anomaly detection in driving behavior means recognizing anomalous driving states as a direct result of either environmental or psychological factors. This paper provid...

Use of deep learning to predict the need for aggressive nutritional supplementation during head and neck radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE/OBJECTIVES: Radiation therapy (RT) for the treatment of patients with head and neck cancer (HNC) leads to side effects that can limit a person's oral intake. Early identification of patients who need aggressive nutrition supplementation via a...

Predicting Neurological Outcome From Electroencephalogram Dynamics in Comatose Patients After Cardiac Arrest With Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Most cardiac arrest patients who are successfully resuscitated are initially comatose due to hypoxic-ischemic brain injury. Quantitative electroencephalography (EEG) provides valuable prognostic information. However, prior approaches large...

Brain Functional Connectivity Analysis via Graphical Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: Graphical deep learning models provide a desirable way for brain functional connectivity analysis. However, the application of current graph deep learning models to brain network analysis is challenging due to the limited sample size and c...

Assessing clinical applicability of COVID-19 detection in chest radiography with deep learning.

Scientific reports
The coronavirus disease 2019 (COVID-19) pandemic has impacted healthcare systems across the world. Chest radiography (CXR) can be used as a complementary method for diagnosing/following COVID-19 patients. However, experience level and workload of tec...

Deep learning-enabled mobile application for efficient and robust herb image recognition.

Scientific reports
With the increasing popularity of herbal medicine, high standards of the high quality control of herbs becomes a necessity, with the herb recognition as one of the great challenges. Due to the complicated processing procedure of the herbs, methods of...

Deep learning for spirometry quality assurance with spirometric indices and curves.

Respiratory research
BACKGROUND: Spirometry quality assurance is a challenging task across levels of healthcare tiers, especially in primary care. Deep learning may serve as a support tool for enhancing spirometry quality. We aimed to develop a high accuracy and sensitiv...

Land Resource Use Classification Using Deep Learning in Ecological Remote Sensing Images.

Computational intelligence and neuroscience
Aiming at the problems that the traditional remote sensing image classification methods cannot effectively integrate a variety of deep learning features and poor classification performance, a land resource use classification method based on a convolu...

Efficient Framework for Detection of COVID-19 Omicron and Delta Variants Based on Two Intelligent Phases of CNN Models.

Computational and mathematical methods in medicine
INTRODUCTION: While the COVID-19 pandemic was waning in most parts of the world, a new wave of COVID-19 Omicron and Delta variants in Central Asia and the Middle East caused a devastating crisis and collapse of health-care systems. As the diagnostic ...