AIMC Topic: Natural Language Processing

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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...

Regularizing transformers with deep probabilistic layers.

Neural networks : the official journal of the International Neural Network Society
Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. However, regularization is not deeply studied in those structures. In this work, we use a Gaussian Mixture Variation...

Using natural language processing to identify child maltreatment in health systems.

Child abuse & neglect
BACKGROUND: Rates of child maltreatment (CM) obtained from electronic health records are much lower than national child welfare prevalence rates indicate. There is a need to understand how CM is documented to improve reporting and surveillance.

Natural Language Processing Basics.

Clinical journal of the American Society of Nephrology : CJASN

Implicit Perception of Differences between NLP-Produced and Human-Produced Language in the Mentalizing Network.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Natural language processing (NLP) is central to the communication with machines and among ourselves, and NLP research field has long sought to produce human-quality language. Identification of informative criteria for measuring NLP-produced language ...

Deep learning approach to detection of colonoscopic information from unstructured reports.

BMC medical informatics and decision making
BACKGROUND: Colorectal cancer is a leading cause of cancer deaths. Several screening tests, such as colonoscopy, can be used to find polyps or colorectal cancer. Colonoscopy reports are often written in unstructured narrative text. The information em...

Extracting medication changes in clinical narratives using pre-trained language models.

Journal of biomedical informatics
An accurate and detailed account of patient medications, including medication changes within the patient timeline, is essential for healthcare providers to provide appropriate patient care. Healthcare providers or the patients themselves may initiate...