AIMC Topic: Natural Language Processing

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Learning Dual Encoding Model for Adaptive Visual Understanding in Visual Dialogue.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue task involves multiple rounds of dialogues which cover a broad range of visual content that could be related to any objects, relat...

Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future studies.

Journal of biomedical semantics
BACKGROUND: Free-text descriptions in electronic health records (EHRs) can be of interest for clinical research and care optimization. However, free text cannot be readily interpreted by a computer and, therefore, has limited value. Natural Language ...

Public Perception of the COVID-19 Pandemic on Twitter: Sentiment Analysis and Topic Modeling Study.

JMIR public health and surveillance
BACKGROUND: COVID-19 is a scientifically and medically novel disease that is not fully understood because it has yet to be consistently and deeply studied. Among the gaps in research on the COVID-19 outbreak, there is a lack of sufficient infoveillan...

Triage of documents containing protein interactions affected by mutations using an NLP based machine learning approach.

BMC genomics
BACKGROUND: Information on protein-protein interactions affected by mutations is very useful for understanding the biological effect of mutations and for developing treatments targeting the interactions. In this study, we developed a natural language...

List-wise learning to rank biomedical question-answer pairs with deep ranking recursive autoencoders.

PloS one
Biomedical question answering (QA) represents a growing concern among industry and academia due to the crucial impact of biomedical information. When mapping and ranking candidate snippet answers within relevant literature, current QA systems typical...

TAPER: Time-Aware Patient EHR Representation.

IEEE journal of biomedical and health informatics
Effective representation learning of electronic health records is a challenging task and is becoming more important as the availability of such data is becoming pervasive. The data contained in these records are irregular and contain multiple modalit...

A recurrent neural network framework for flexible and adaptive decision making based on sequence learning.

PLoS computational biology
The brain makes flexible and adaptive responses in a complicated and ever-changing environment for an organism's survival. To achieve this, the brain needs to understand the contingencies between its sensory inputs, actions, and rewards. This is anal...

Interactive Dual Attention Network for Text Sentiment Classification.

Computational intelligence and neuroscience
Text sentiment classification is an essential research field of natural language processing. Recently, numerous deep learning-based methods for sentiment classification have been proposed and achieved better performances compared with conventional ma...

Prediction of breast cancer distant recurrence using natural language processing and knowledge-guided convolutional neural network.

Artificial intelligence in medicine
Distant recurrence of breast cancer results in high lifetime risks and low 5-year survival rates. Early prediction of distant recurrent breast cancer could facilitate intervention and improve patients' life quality. In this study, we designed an EHR-...

Text Classification for Clinical Trial Operations: Evaluation and Comparison of Natural Language Processing Techniques.

Therapeutic innovation & regulatory science
The ability to detect patterns and trends across protocol deviations (PDs) is key to ensure high data quality and sufficient oversight of patient safety. In clinical trial operations, some business processes and work instructions limit efficient prot...