AIMC Topic: Humans

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Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm.

Critical care (London, England)
BACKGROUND: Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some pr...

Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery.

Radiation oncology (London, England)
BACKGROUND: In breast cancer patients receiving radiotherapy (RT), accurate target delineation and reduction of radiation doses to the nearby normal organs is important. However, manual clinical target volume (CTV) and organs-at-risk (OARs) segmentat...

Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

Journal of neuroengineering and rehabilitation
BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculatur...

Low-dose PET image noise reduction using deep learning: application to cardiac viability FDG imaging in patients with ischemic heart disease.

Physics in medicine and biology
INTRODUCTION: Cardiac [F]FDG-PET is widely used for viability testing in patients with chronic ischemic heart disease. Guidelines recommend injection of 200-350 MBq [F]FDG, however, a reduction of radiation exposure has become increasingly important,...

COVID-19 in Iran: Forecasting Pandemic Using Deep Learning.

Computational and mathematical methods in medicine
COVID-19 has led to a pandemic, affecting almost all countries in a few months. In this work, we applied selected deep learning models including multilayer perceptron, random forest, and different versions of long short-term memory (LSTM), using thre...

Monitoring social distancing under various low light conditions with deep learning and a single motionless time of flight camera.

PloS one
The purpose of this work is to provide an effective social distance monitoring solution in low light environments in a pandemic situation. The raging coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus has brought a global crisis with ...

A dataset of human and robot approach behaviors into small free-standing conversational groups.

PloS one
The analysis and simulation of the interactions that occur in group situations is important when humans and artificial agents, physical or virtual, must coordinate when inhabiting similar spaces or even collaborate, as in the case of human-robot team...

Gaussian smoothing and modified histogram normalization methods to improve neural-biomarker interpretations for dyslexia classification mechanism.

PloS one
Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heter...

A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis.

PloS one
The spread of Covid-19 has resulted in worldwide health concerns. Social media is increasingly used to share news and opinions about it. A realistic assessment of the situation is necessary to utilize resources optimally and appropriately. In this re...

Revealing posturographic profile of patients with Parkinsonian syndromes through a novel hypothesis testing framework based on machine learning.

PloS one
Falling in Parkinsonian syndromes (PS) is associated with postural instability and consists a common cause of disability among PS patients. Current posturographic practices record the body's center-of-pressure displacement (statokinesigram) while the...