AIMC Topic: Deep Learning

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A Hybrid Deep Learning and Visualization Framework for Pushing Behavior Detection in Pedestrian Dynamics.

Sensors (Basel, Switzerland)
Crowded event entrances could threaten the comfort and safety of pedestrians, especially when some pedestrians push others or use gaps in crowds to gain faster access to an event. Studying and understanding pushing dynamics leads to designing and bui...

Development of a deep learning model that predicts Bi-level positive airway pressure failure.

Scientific reports
Delaying intubation for patients failing Bi-Level Positive Airway Pressure (BIPAP) may be associated with harm. The objective of this study was to develop a deep learning model capable of aiding clinical decision making by predicting Bi-Level Positiv...

Deep learning-based automated segmentation of eight brain anatomical regions using head CT images in PET/CT.

BMC medical imaging
OBJECTIVE: We aim to propose a deep learning-based method of automated segmentation of eight brain anatomical regions in head computed tomography (CT) images obtained during positron emission tomography/computed tomography (PET/CT) scans. The brain r...

Dual-energy CT based mass density and relative stopping power estimation for proton therapy using physics-informed deep learning.

Physics in medicine and biology
Proton therapy requires accurate dose calculation for treatment planning to ensure the conformal doses are precisely delivered to the targets. The conversion of CT numbers to material properties is a significant source of uncertainty for dose calcula...

Decoding neural activity preceding balance loss during standing with a lower-limb exoskeleton using an interpretable deep learning model.

Journal of neural engineering
Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require ear...

Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model.

Computational intelligence and neuroscience
In today's world, diabetic retinopathy is a very severe health issue, which is affecting many humans of different age groups. Due to the high levels of blood sugar, the minuscule blood vessels in the retina may get damaged in no time and further may ...

Deep Learning-Based Postoperative Recovery and Nursing of Total Hip Arthroplasty.

Computational and mathematical methods in medicine
OBJECTIVE: To develop a deep learning-assisted recovery and nursing system after total hip arthroplasty and to conduct clinical trials in order to verify its accuracy.

Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning-based convolutional neural network algorithm.

Oral radiology
OBJECTIVES: Artificial intelligence (AI) techniques like convolutional neural network (CNN) are a promising breakthrough that can help clinicians analyze medical imaging, diagnose taurodontism, and make therapeutic decisions. The purpose of the study...

Scoping review and classification of deep learning in medical genetics.

Genetics in medicine : official journal of the American College of Medical Genetics
Deep learning (DL) is applied in many biomedical areas. We performed a scoping review on DL in medical genetics. We first assessed 14,002 articles, of which 133 involved DL in medical genetics. DL in medical genetics increased rapidly during the stud...

Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning.

Acta biomaterialia
Microstructural features and mechanical properties are closely related in all soft biological tissues. Both yet exhibit considerable inter-individual differences and are affected by factors such as aging and disease and its progression. Histological ...