AIMC Topic: Natural Language Processing

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Integrating machine learning with linguistic features: A universal method for extraction and normalization of temporal expressions in Chinese texts.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: With the rapid development of information dissemination technology, the amount of events information contained in massive texts now far exceeds the intuitive cognition of humans, and it is hard to understand the progress of ...

A Natural Language Processing Model to Identify Confidential Content in Adolescent Clinical Notes.

Applied clinical informatics
BACKGROUND: The 21st Century Cures Act mandates the immediate, electronic release of health information to patients. However, in the case of adolescents, special consideration is required to ensure that confidentiality is maintained. The detection of...

Natural language processing in radiology: Clinical applications and future directions.

Clinical imaging
Natural language processing (NLP) is a wide range of techniques that allows computers to interact with human text. Applications of NLP in everyday life include language translation aids, chat bots, and text prediction. It has been increasingly utiliz...

Assessment of Natural Language Processing of Electronic Health Records to Measure Goals-of-Care Discussions as a Clinical Trial Outcome.

JAMA network open
IMPORTANCE: Many clinical trial outcomes are documented in free-text electronic health records (EHRs), making manual data collection costly and infeasible at scale. Natural language processing (NLP) is a promising approach for measuring such outcomes...

An Alternative Application of Natural Language Processing to Express a Characteristic Feature of Diseases in Japanese Medical Records.

Methods of information in medicine
BACKGROUND: Owing to the linguistic situation, Japanese natural language processing (NLP) requires morphological analyses for word segmentation using dictionary techniques.

Let the algorithm speak: How to use neural networks for automatic item generation in psychological scale development.

Psychological methods
Measurement is at the heart of scientific research. As many-perhaps most-psychological constructs cannot be directly observed, there is a steady demand for reliable self-report scales to assess latent constructs. However, scale development is a tedio...

Letter to editor: NLP systems such as ChatGPT cannot be listed as an author because these cannot fulfill widely adopted authorship criteria.

Accountability in research
This letter to the editor suggests adding a technical point to the new editorial policy expounded by Hosseini et al. on the mandatory disclosure of any use of natural language processing (NLP) systems, or generative AI, in writing scholarly publicati...

Development and testing of a multi-lingual Natural Language Processing-based deep learning system in 10 languages for COVID-19 pandemic crisis: A multi-center study.

Frontiers in public health
PURPOSE: The COVID-19 pandemic has drastically disrupted global healthcare systems. With the higher demand for healthcare and misinformation related to COVID-19, there is a need to explore alternative models to improve communication. Artificial Intel...

Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review.

Computers in biology and medicine
BACKGROUND: Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. V...