AIMC Topic: Humans

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CXR-RefineDet: Single-Shot Refinement Neural Network for Chest X-Ray Radiograph Based on Multiple Lesions Detection.

Journal of healthcare engineering
The workload of radiologists has dramatically increased in the context of the COVID-19 pandemic, causing misdiagnosis and missed diagnosis of diseases. The use of artificial intelligence technology can assist doctors in locating and identifying lesio...

Design-Centered HRI Governance for Healthcare Robots.

Journal of healthcare engineering
Recent developments have shown that not only are AI and robotics growing more sophisticated, but also these fields are evolving together. The applications that emerge from this trend will break current limitations and ensure that robotic decision mak...

Computed Tomography Image Features under Deep Learning Algorithm Applied in Staging Diagnosis of Bladder Cancer and Detection on Ceramide Glycosylation.

Computational and mathematical methods in medicine
The research is aimed at investigating computed tomography (CT) image based on deep learning algorithm and the application value of ceramide glycosylation in diagnosing bladder cancer. The images of ordinary CT detection were improved. In this study,...

Zoomorphic Mobile Robot Development for Vertical Movement Based on the Geometrical Family Caterpillar.

Computational intelligence and neuroscience
Research in robotics is one of the promising areas in mobile robot development, which is planned to be implemented in extreme dangerous conditions of areas explored by humans. This article aims at developing and improving a prototype of zoomorphic mo...

Advanced Deep Learning Human Herpes Virus 6 (HHV-6) Molecular Detection in Understanding Human Infertility.

Computational intelligence and neuroscience
To see if HHV-6 may be a cause of infertility, researchers looked at 18 men and 10 women who had unexplained critical fertility and had at least one prior pregnancy. HHV-6 DNA was discovered in both infertile and fertile peripheral blood mononuclear ...

A Novel Framework Based on Deep Learning and ANOVA Feature Selection Method for Diagnosis of COVID-19 Cases from Chest X-Ray Images.

Computational intelligence and neuroscience
. The new coronavirus disease (known as COVID-19) was first identified in Wuhan and quickly spread worldwide, wreaking havoc on the economy and people's everyday lives. As the number of COVID-19 cases is rapidly increasing, a reliable detection techn...

A deep neural network model for multi-view human activity recognition.

PloS one
Multiple cameras are used to resolve occlusion problem that often occur in single-view human activity recognition. Based on the success of learning representation with deep neural networks (DNNs), recent works have proposed DNNs models to estimate hu...

Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories.

PloS one
BACKGROUND: Forensic dentistry identifies deceased individuals by comparing postmortem dental charts, oral-cavity pictures and dental X-ray images with antemortem records. However, conventional forensic dentistry methods are time-consuming and thus u...

Identification of an early-stage Parkinson's disease neuromarker using event-related potentials, brain network analytics and machine-learning.

PloS one
OBJECTIVE: The purpose of this study is to explore the possibility of developing a biomarker that can discriminate early-stage Parkinson's disease from healthy brain function using electroencephalography (EEG) event-related potentials (ERPs) in combi...

Increasing neural network robustness improves match to macaque V1 eigenspectrum, spatial frequency preference and predictivity.

PLoS computational biology
Task-optimized convolutional neural networks (CNNs) show striking similarities to the ventral visual stream. However, human-imperceptible image perturbations can cause a CNN to make incorrect predictions. Here we provide insight into this brittleness...