The classic dynamic autoregulatory index (ARI), proposed by Aaslid and Tiecks, is one of the most widely used methods to assess the efficiency of dynamic cerebral autoregulation. Although this index is often used in clinical research and is also …
This paper shows a preliminary study to perform a pattern recognition process for seismic events of the Llaima volcano, one of the most active volcanoes in South America. 1622 classified events registered from the Llaima volcano were considered in …
This paper proposes a computer-based classifier to automatically identify four seismic event classes of the Llaima volcano, one of the most active volcanoes in the Southern Andes, situated in the Araucanía Region of Chile. A combination of features …
Objective. Incorporating high-frequency components in transcutaneous electrical stimulation (TES) waveforms may make it possible to stimulate deeper nerve fibers since the impedance of tissue declines with increasing frequency. However, the …
A novel method is described for mapping dynamic cerebral blood flow autoregulation to assess autoregulatory efficiency throughout the brain, using magnetic resonance imaging (MRI). Global abnormalities in autoregulation occur in clinical conditions, …
The presented work proposes a new approach for anomaly detection. This approach is based on changes in a population of evolving agents under stress. If conditions are appropriate, changes in the population (modeled by the bioindicators) are …
Background: Short-segment Barrett's esophagus (SSBE) or long-segment Barrett's esophagus (LSBE) is the consequence of chronic gastroesophageal reflux disease (GERD), which is frequently associated with obesity. Obesity is a significant risk factor …
Artificial sensation via electrical or optical stimulation of brain sensory areas offers a promising treatment for sensory deficits. For a brain-machine-brain interface, such artificial sensation conveys feedback signals from a sensorized prosthetic …
Diagnoses are a valuable source of information for evaluating a health system. However, they are not used extensively by information systems because diagnoses are normally written in natural language. This work empirically evaluates three machine …
Since the appearance of methods based on machine learning, they have been presented as an alternative to classical phenomenological modeling and there are few initiatives that attempt to integrate them. This paper presents a hybrid paradigm called …