BMC medical informatics and decision making
Dec 23, 2019
BACKGROUND: The medical community uses a variety of data standards for both clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) represent one such standard that provides robust data point definitions. Another standard is the ...
Computational intelligence and neuroscience
Dec 19, 2019
Aspect-level sentiment classification aims to identify the sentiment polarity of a review expressed toward a target. In recent years, neural network-based methods have achieved success in aspect-level sentiment classification, and these methods fall ...
BMC medical informatics and decision making
Dec 12, 2019
BACKGROUND: The automatic segmentation of kidneys in medical images is not a trivial task when the subjects undergoing the medical examination are affected by Autosomal Dominant Polycystic Kidney Disease (ADPKD). Several works dealing with the segmen...
BMC medical informatics and decision making
Dec 5, 2019
BACKGROUND: Machine learning can assist with multiple tasks during systematic reviews to facilitate the rapid retrieval of relevant references during screening and to identify and extract information relevant to the study characteristics, which inclu...
BMC medical informatics and decision making
Dec 5, 2019
BACKGROUND: Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number of professional and uncommon...
BMC medical informatics and decision making
Dec 5, 2019
BACKGROUND: Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful relationships between entities au...
This paper offers a new way of considering places as special types of categories, in human cognition of larger-scale environments. This may provide an explanatory cognitive model for a range of known phenomena from environmental psychology and human ...
Traditional general linear model-based brain mapping efforts using functional neuroimaging are complemented by more recent multivariate pattern analyses (MVPA) that apply machine learning techniques to identify the cognitive states associated with re...
Causal graphs play an essential role in the determination of causalities and have been applied in many domains including biology and medicine. Traditional causal graph construction methods are usually data-driven and may not deliver the desired accur...
In this paper, using Word2vec, a widely-used natural language processing method, we demonstrate that protein domains may have a learnable implicit semantic "meaning" in the context of their functional contributions to the multi-domain proteins in whi...