AIMC Topic: Humans

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Stress State Classification Based on Deep Neural Network and Electrodermal Activity Modeling.

Sensors (Basel, Switzerland)
Electrodermal Activity (EDA) has become of great interest in the last several decades, due to the advent of new devices that allow for recording a lot of psychophysiological data for remotely monitoring patients' health. In this work, a novel method ...

Fiber Bundle Image Reconstruction Using Convolutional Neural Networks and Bundle Rotation in Endomicroscopy.

Sensors (Basel, Switzerland)
Fiber-bundle endomicroscopy has several recognized drawbacks, the most prominent being the honeycomb effect. We developed a multi-frame super-resolution algorithm exploiting bundle rotation to extract features and reconstruct underlying tissue. Simul...

Cross-Domain Transfer of EEG to EEG or ECG Learning for CNN Classification Models.

Sensors (Basel, Switzerland)
Electroencephalography (EEG) is often used to evaluate several types of neurological brain disorders because of its noninvasive and high temporal resolution. In contrast to electrocardiography (ECG), EEG can be uncomfortable and inconvenient for pati...

Research on Evaluation of University Emergency Management Ability Based on BP Neural Network.

International journal of environmental research and public health
University emergency management ability is an important part of university safety management. To evaluate university emergency management ability scientifically, objectively, and accurately, this study constructs three first-level indexes, namely, pr...

Abstract representations emerge naturally in neural networks trained to perform multiple tasks.

Nature communications
Humans and other animals demonstrate a remarkable ability to generalize knowledge across distinct contexts and objects during natural behavior. We posit that this ability to generalize arises from a specific representational geometry, that we call ab...

Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol.

BMJ open
INTRODUCTION: Artificial intelligence (AI), the simulation of human intelligence processes by machines, is being increasingly leveraged to facilitate clinical decision-making. AI-based clinical decision support (CDS) tools can improve the quality of ...

Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.

Physics in medicine and biology
. The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmentation compared with standard manual delineation for postoperative cervical cancer.. We introduced a c...

Deep learning aided oropharyngeal cancer segmentation with adaptive thresholding for predicted tumor probability in FDG PET and CT images.

Physics in medicine and biology
 Tumor segmentation is a fundamental step for radiotherapy treatment planning. To define an accurate segmentation of the primary tumor (GTVp) of oropharyngeal cancer patients (OPC) each image volume is explored slice-by-slice from different orientati...

Deep learning for the diagnosis of mesial temporal lobe epilepsy.

PloS one
OBJECTIVE: This study aimed to enable the automatic detection of the hippocampus and diagnose mesial temporal lobe epilepsy (MTLE) with the hippocampus as the epileptogenic area using artificial intelligence (AI). We compared the diagnostic accuracie...

Dynamic risk assessment of hospital oxygen supply system by HAZOP and intuitionistic fuzzy.

PloS one
Events such as oxygen leakage in the oxygen generation systems can have severe consequences, such as fire and explosion. In addition, the disruption in the oxygenation systems can lead to a threat to patients' lives. Thus, this study aimed to identif...