The free-form portions of clinical notes are a significant source of information for research, but before they can be used, they must be de-identified to protect patients' privacy. De-identification efforts have focused on known identifier types (nam...
BACKGROUND: MicroRNAs (miRNAs) are a family of short, non-coding RNAs that have been linked to critical cellular activities, most notably regulation of gene expression. The identification of miRNA is a cross-disciplinary approach that requires both c...
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...
Being medical students, and having experienced different learning approaches ourselves, here, we discuss and critically analyse the importance of the deep learning approach that Chonkar et al. have presented, alongside emphasizing Case Based Learning...
International journal of medical informatics
Dec 23, 2017
BACKGROUND: Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emer...
International journal of medical informatics
Aug 5, 2017
OBJECTIVE: To investigate: (1) the annotation time savings by various active learning query strategies compared to supervised learning and a random sampling baseline, and (2) the benefits of active learning-assisted pre-annotations in accelerating th...
BMC medical informatics and decision making
Jul 5, 2017
BACKGROUND: Active learning (AL) has shown the promising potential to minimize the annotation cost while maximizing the performance in building statistical natural language processing (NLP) models. However, very few studies have investigated AL in a ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Feb 10, 2017
Resolving word ambiguity in clinical text is critical for many natural language processing applications. Effective word sense disambiguation (WSD) systems rely on training a machine learning based classifier with abundant clinical text that is accura...
Coping with scarcity of labeled data is a common problem in sound classification tasks. Approaches for classifying sounds are commonly based on supervised learning algorithms, which require labeled data which is often scarce and leads to models that ...
Journal of the American Medical Informatics Association : JAMIA
Aug 7, 2015
OBJECTIVE: This paper presents an automatic, active learning-based system for the extraction of medical concepts from clinical free-text reports. Specifically, (1) the contribution of active learning in reducing the annotation effort and (2) the robu...
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