The identification of medical concepts, their attributes and the relations between concepts in a large corpus of Electroencephalography (EEG) reports is a crucial step in the development of an EEG-specific patient cohort retrieval system. However, th...
BACKGROUND: Free-text imposes a challenge in health data analysis since the lack of structure makes the extraction and integration of information difficult, particularly in the case of massive data. An appropriate machine-interpretation of electronic...
Dmitri Strukov (an electrical engineer, University of California at Santa Barbara), Giacomo Indiveri (an electrical engineer, University of Zurich), Julie Grollier (a material physicist, Unite Mixte de Physique CNRS) and Stefano Fusi (a neuroscientis...
IMPORTANCE: Automatic curation of consumer-generated, opioid-related social media big data may enable real-time monitoring of the opioid epidemic in the United States.
The ability to rapidly assimilate new information is essential for survival in a dynamic environment. This requires experiences to be encoded alongside the contextual schemas in which they occur. Tse et al. (Science 316(5821):76-82, 2007) showed that...
International journal of medical informatics
32172185
OBJECTIVE: The majority of radiological reports are still written as free text and lack structure. Further evaluation of free-text reports is difficult to achieve without a great deal of manual effort, and is not possible in everyday clinical practic...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
32146425
Simultaneous detection of biomarkers and biomolecules with great analytical performance still is challenging. A simple fluorometric dual-functional aptasensor was designed to detect Lysozyme (LYS) and adenosine triphosphate (ATP) as models of a prote...
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, which limit both accuracy and throughput. To address this, we developed a deep learning-based image an...
IEEE transactions on neural networks and learning systems
32054587
This article proposes an unsupervised address event representation (AER) object recognition approach. The proposed approach consists of a novel multiscale spatio-temporal feature (MuST) representation of input AER events and a spiking neural network ...
IEEE transactions on neural networks and learning systems
32324576
In this article, by introducing a signed graph to describe the coopetition interactions among network nodes, the mathematical model of multiple memristor-based neural networks (MMNNs) with antagonistic interactions is established. Since the cooperati...