AIMC Topic: Humans

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Neurophysiological brain mapping of human sleep-wake states.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: We recently proposed a spectrum-based model of the awake intracranial electroencephalogram (iEEG) (Kalamangalam et al., 2020), based on a publicly-available normative database (Frauscher et al., 2018). The latter has been expanded to inclu...

CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification.

Medical image analysis
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science problem. We de...

A deep learning based surrogate model for the parameter identification problem in probabilistic cellular automaton epidemic models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: an accurate estimation of the epidemiological model coefficients helps understand the basic principles of disease spreading. Some studies showed that dozens of hours are needed to simulate the traditional probabilistic cellu...

A knowledge base of clinical trial eligibility criteria.

Journal of biomedical informatics
OBJECTIVE: We present the Clinical Trial Knowledge Base, a regularly updated knowledge base of discrete clinical trial eligibility criteria equipped with a web-based user interface for querying and aggregate analysis of common eligibility criteria.

Echocardiographic image multi-structure segmentation using Cardiac-SegNet.

Medical physics
PURPOSE: Cardiac boundary segmentation of echocardiographic images is important for cardiac function assessment and disease diagnosis. However, it is challenging to segment cardiac ventricles due to the low contrast-to-noise ratio and speckle noise o...

Text-Guided Neural Network Training for Image Recognition in Natural Scenes and Medicine.

IEEE transactions on pattern analysis and machine intelligence
Convolutional neural networks (CNNs) are widely recognized as the foundation for machine vision systems. The conventional rule of teaching CNNs to understand images requires training images with human annotated labels, without any additional instruct...

Artificial Intelligence in Hypertension: Seeing Through a Glass Darkly.

Circulation research
Hypertension remains the largest modifiable cause of mortality worldwide despite the availability of effective medications and sustained research efforts over the past 100 years. Hypertension requires transformative solutions that can help reduce the...

Artificial Intelligence Efficiently Identifies Regional Differences in the Progression of Tomographic Parameters of Keratoconic Corneas.

Journal of refractive surgery (Thorofare, N.J. : 1995)
PURPOSE: To develop an artificial intelligence (AI) model to effectively assess local versus global progression of keratoconus using multiple tomographic parameters.

Vision and RTLS Safety Implementation in an Experimental Human-Robot Collaboration Scenario.

Sensors (Basel, Switzerland)
Human-robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. Th...