AIMC Topic: Humans

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Convolutional neural networks for PET functional volume fully automatic segmentation: development and validation in a multi-center setting.

European journal of nuclear medicine and molecular imaging
PURPOSE: In this work, we addressed fully automatic determination of tumor functional uptake from positron emission tomography (PET) images without relying on other image modalities or additional prior constraints, in the context of multicenter image...

Real-time face & eye tracking and blink detection using event cameras.

Neural networks : the official journal of the International Neural Network Society
Event cameras contain emerging, neuromorphic vision sensors that capture local-light​ intensity changes at each pixel, generating a stream of asynchronous events. This way of acquiring visual information constitutes a departure from traditional frame...

Predicting Length of Stay of Coronary Artery Bypass Grafting Patients Using Machine Learning.

The Journal of surgical research
BACKGROUND: There is a growing need to identify which bits of information are most valuable for healthcare providers. The aim of this study was to search for the highest impact variables in predicting postsurgery length of stay (LOS) for patients who...

Characterizing the function of domain linkers in regulating the dynamics of multi-domain fusion proteins by microsecond molecular dynamics simulations and artificial intelligence.

Proteins
Multi-domain proteins are not only formed through natural evolution but can also be generated by recombinant DNA technology. Because many fusion proteins can enhance the selectivity of cell targeting, these artificially produced molecules, called mul...

Detecting the Early Infarct Core on Non-Contrast CT Images with a Deep Learning Residual Network.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PURPOSE: To explore a new approach mainly based on deep learning residual network (ResNet) to detect infarct cores on non-contrast CT images and improve the accuracy of acute ischemic stroke diagnosis.

An automated COVID-19 detection based on fused dynamic exemplar pyramid feature extraction and hybrid feature selection using deep learning.

Computers in biology and medicine
The new coronavirus disease known as COVID-19 is currently a pandemic that is spread out the whole world. Several methods have been presented to detect COVID-19 disease. Computer vision methods have been widely utilized to detect COVID-19 by using ch...

Attention-Based Temporal Encoding Network with Background-Independent Motion Mask for Action Recognition.

Computational intelligence and neuroscience
Convolutional neural network (CNN) has been leaping forward in recent years. However, the high dimensionality, rich human dynamic characteristics, and various kinds of background interference increase difficulty for traditional CNNs in capturing comp...

Determining suitable machine learning classifier technique for prediction of malaria incidents attributed to climate of Odisha.

International journal of environmental health research
This study investigated the influence of climate factors on malaria incidence in the Sundargarh district, Odisha, India. The WEKA machine learning tool was used with two classifier techniques, Multi-Layer Perceptron (MLP) and J48, with three test opt...

Selective Suturing or Sutureless Technique in Robot-assisted Partial Nephrectomy: Results from a Propensity-score Matched Analysis.

European urology focus
BACKGROUND: Despite efforts aimed at preserving renal function, the functional decline after robot-assisted partial nephrectomy (RAPN) is not negligible. To address the risk of intraparenchymal vessel injuries during renorrhaphy, with consequent loss...