AIMC Topic: Natural Language Processing

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MAGPEL: an autoMated pipeline for inferring vAriant-driven Gene PanEls from the full-length biomedical literature.

Scientific reports
In spite of the efforts in developing and maintaining accurate variant databases, a large number of disease-associated variants are still hidden in the biomedical literature. Curation of the biomedical literature in an effort to extract this informat...

Understanding the spatial dimension of natural language by measuring the spatial semantic similarity of words through a scalable geospatial context window.

PloS one
Measuring the semantic similarity between words is important for natural language processing tasks. The traditional models of semantic similarity perform well in most cases, but when dealing with words that involve geographical context, spatial seman...

Time-distanced gates in long short-term memory networks.

Medical image analysis
The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging from natural language processing to medical imaging. The LSTM has shown promise for interpreting computed tomography (CT) in lung screening...

Exploring the Privacy-Preserving Properties of Word Embeddings: Algorithmic Validation Study.

Journal of medical Internet research
BACKGROUND: Word embeddings are dense numeric vectors used to represent language in neural networks. Until recently, there had been no publicly released embeddings trained on clinical data. Our work is the first to study the privacy implications of r...

Extraction of temporal relations from clinical free text: A systematic review of current approaches.

Journal of biomedical informatics
BACKGROUND: Temporal relations between clinical events play an important role in clinical assessment and decision making. Extracting such relations from free text data is a challenging task because it lies on between medical natural language processi...

Cross-Modal Search for Social Networks via Adversarial Learning.

Computational intelligence and neuroscience
Cross-modal search has become a research hotspot in the recent years. In contrast to traditional cross-modal search, social network cross-modal information search is restricted by data quality for arbitrary text and low-resolution visual features. In...

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Journal of biomedical informatics
Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Suc...