AIMC Topic: Natural Language Processing

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Precision Assessment of COVID-19 Phenotypes Using Large-Scale Clinic Visit Audio Recordings: Harnessing the Power of Patient Voice.

Journal of medical Internet research
COVID-19 cases are exponentially increasing worldwide; however, its clinical phenotype remains unclear. Natural language processing (NLP) and machine learning approaches may yield key methods to rapidly identify individuals at a high risk of COVID-19...

Automated classification of cancer morphology from Italian pathology reports using Natural Language Processing techniques: A rule-based approach.

Journal of biomedical informatics
Pathology reports represent a primary source of information for cancer registries. Hospitals routinely process high volumes of free-text reports, a valuable source of information regarding cancer diagnosis for improving clinical care and supporting r...

Effects of age and sex on the distribution and symmetry of lumbar spinal and neural foraminal stenosis: a natural language processing analysis of 43,255 lumbar MRI reports.

Neuroradiology
PURPOSE: The purpose of this study is to investigate relationship of patient age and sex to patterns of degenerative spinal stenosis on lumbar MRI (LMRI), rated as moderate or greater by a spine radiologist, using natural language processing (NLP) to...

Emotion Detection for Social Robots Based on NLP Transformers and an Emotion Ontology.

Sensors (Basel, Switzerland)
For social robots, knowledge regarding human emotional states is an essential part of adapting their behavior or associating emotions to other entities. Robots gather the information from which emotion detection is processed via different media, such...

Evolutionary Algorithm based Ensemble Extractive Summarization for Developing Smart Medical System.

Interdisciplinary sciences, computational life sciences
The amount of information in the scientific literature of the bio-medical domain is growing exponentially, which makes it difficult in developing a smart medical system. Summarization techniques help for efficient searching and understanding of relev...

Technical Note: An embedding-based medical note de-identification approach with sparse annotation.

Medical physics
PURPOSE: Medical note de-identification is critical for the protection of private information and the security of data sharing in collaborative research. The task demands the complete removal of all patient names and other sensitive information such ...

Comparative study using inverse ontology cogency and alternatives for concept recognition in the annotated National Library of Medicine database.

Neural networks : the official journal of the International Neural Network Society
This paper introduces inverse ontology cogency, a concept recognition process and distance function that is biologically-inspired and competitive with alternative methods. The paper introduces inverse ontology cogency as a new alternative method. It ...

Modeling the predictive potential of extralinguistic context with script knowledge: The case of fragments.

PloS one
We describe a novel approach to estimating the predictability of utterances given extralinguistic context in psycholinguistic research. Predictability effects on language production and comprehension are widely attested, but so far predictability has...

GT-Finder: Classify the family of glucose transporters with pre-trained BERT language models.

Computers in biology and medicine
Recently, language representation models have drawn a lot of attention in the field of natural language processing (NLP) due to their remarkable results. Among them, BERT (Bidirectional Encoder Representations from Transformers) has proven to be a si...