AIMC Topic: Natural Language Processing

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Vision-referential speech enhancement of an audio signal using mask information captured as visual data.

The Journal of the Acoustical Society of America
This paper describes a vision-referential speech enhancement of an audio signal using mask information captured as visual data. Smartphones and tablet devices have become popular in recent years. Most of them not only have a microphone but also a cam...

Detecting Adverse Drug Events with Rapidly Trained Classification Models.

Drug safety
INTRODUCTION: Identifying occurrences of medication side effects and adverse drug events (ADEs) is an important and challenging task because they are frequently only mentioned in clinical narrative and are not formally reported.

Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

Drug safety
INTRODUCTION: This work describes the Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0) corpus and provides an overview of the MADE 1.0 2018 challenge for extracting medication, indication, and adverse drug events (ADEs) fr...

Incorporating Demographic Embeddings Into Language Understanding.

Cognitive science
Meaning depends on context. This applies in obvious cases like deictics or sarcasm as well as more subtle situations like framing or persuasion. One key aspect of this is the identity of the participants in an interaction. Our interpretation of an ut...

[Deep Learning and Natural Language Processing].

Brain and nerve = Shinkei kenkyu no shinpo
The field of natural language processing (NLP) has seen rapid advances in the past several years since the introduction of deep learning techniques. A variety of NLP tasks including syntactic parsing, machine translation, and summarization can now be...

[Medical Natural Language Processing for Japanese Language].

Brain and nerve = Shinkei kenkyu no shinpo
Artificial Intelligence technologies are recently attracting attentions. More medical information is available including inspection results and health records of numbers, images and documents, also including audio and video information of subjects. I...

MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes.

Drug safety
INTRODUCTION: Early detection of adverse drug events (ADEs) from electronic health records is an important, challenging task to support pharmacovigilance and drug safety surveillance. A well-known challenge to use clinical text for detection of ADEs ...

Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

Journal of clinical gastroenterology
OBJECTIVES: The aim of this study was to test the ability of a commercially available natural language processing (NLP) tool to accurately extract examination quality-related and large polyp information from colonoscopy reports with varying report fo...

Deep Learning for Natural Language Processing in Urology: State-of-the-Art Automated Extraction of Detailed Pathologic Prostate Cancer Data From Narratively Written Electronic Health Records.

JCO clinical cancer informatics
PURPOSE: Entering all information from narrative documentation for clinical research into databases is time consuming, costly, and nearly impossible. Even high-volume databases do not cover all patient characteristics and drawn results may be limited...

Monitoring of Technology Adoption Using Web Content Mining of Location Information and Geographic Information Systems: A Case Study of Digital Breast Tomosynthesis.

JCO clinical cancer informatics
PURPOSE: To our knowledge, integration of Web content mining of publicly available addresses with a geographic information system (GIS) has not been applied to the timely monitoring of medical technology adoption. Here, we explore the diffusion of a ...