AIMC Topic: Natural Language Processing

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Triangulation of Questionnaires, Qualitative Data and Natural Language Processing: A Differential Approach to Religious Bahá'í Fasting in Germany.

Journal of religion and health
Approaches to integrating mixed methods into medical research are gaining popularity. To get a holistic understanding of the effects of behavioural interventions, we investigated religious fasting using a triangulation of quantitative, qualitative, a...

Using natural language processing to increase prediction and reduce subgroup differences in personnel selection decisions.

The Journal of applied psychology
The purpose of this research is to demonstrate how using natural language processing (NLP) on narrative application data can improve prediction and reduce racial subgroup differences in scores used for selection decisions compared to mental ability t...

Europe PMC annotated full-text corpus for gene/proteins, diseases and organisms.

Scientific data
Named entity recognition (NER) is a widely used text-mining and natural language processing (NLP) subtask. In recent years, deep learning methods have superseded traditional dictionary- and rule-based NER approaches. A high-quality dataset is essenti...

Can ChatGPT be the Plastic Surgeon's New Digital Assistant? A Bibliometric Analysis and Scoping Review of ChatGPT in Plastic Surgery Literature.

Aesthetic plastic surgery
BACKGROUND: ChatGPT, an artificial intelligence (AI) chatbot that uses natural language processing (NLP) to interact in a humanlike manner, has made significant contributions to various healthcare fields, including plastic surgery. However, its wides...

Natural language processing for identification of refractory status epilepticus in children.

Epilepsia
OBJECTIVE: Pediatric status epilepticus is one of the most frequent pediatric emergencies, with high mortality and morbidity. Utilizing electronic health records (EHRs) permits analysis of care approaches and disease outcomes at a lower cost than pro...

MMBERT: a unified framework for biomedical named entity recognition.

Medical & biological engineering & computing
Named entity recognition (NER) is an important task in natural language processing (NLP). In recent years, NER has attracted much attention in the biomedical field. However, due to the lack of biomedical named entity identification datasets, the comp...

AC-PLT: An algorithm for computer-assisted coding of semantic property listing data.

Behavior research methods
In this paper, we present a novel algorithm that uses machine learning and natural language processing techniques to facilitate the coding of feature listing data. Feature listing is a method in which participants are asked to provide a list of featu...

Negation recognition in clinical natural language processing using a combination of the NegEx algorithm and a convolutional neural network.

BMC medical informatics and decision making
BACKGROUND: Important clinical information of patients is present in unstructured free-text fields of Electronic Health Records (EHRs). While this information can be extracted using clinical Natural Language Processing (cNLP), the recognition of nega...

Natural Language Processing Applied to Clinical Documentation in Post-acute Care Settings: A Scoping Review.

Journal of the American Medical Directors Association
OBJECTIVES: To determine the scope of the application of natural language processing to free-text clinical notes in post-acute care and provide a foundation for future natural language processing-based research in these settings.