AIMC Topic: Natural Language Processing

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Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

Psychiatry research
BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

Natural language processing with machine learning methods to analyze unstructured patient-reported outcomes derived from electronic health records: A systematic review.

Artificial intelligence in medicine
OBJECTIVE: Natural language processing (NLP) combined with machine learning (ML) techniques are increasingly used to process unstructured/free-text patient-reported outcome (PRO) data available in electronic health records (EHRs). This systematic rev...

Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.

BMC bioinformatics
BACKGROUND: During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural lang...

Word differences in news media of lower and higher peace countries revealed by natural language processing and machine learning.

PloS one
Language is both a cause and a consequence of the social processes that lead to conflict or peace. "Hate speech" can mobilize violence and destruction. What are the characteristics of "peace speech" that reflect and support the social processes that ...

Current Strengths and Weaknesses of ChatGPT as a Resource for Radiation Oncology Patients and Providers.

International journal of radiation oncology, biology, physics
PURPOSE: Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence program that uses natural language processing to generate conversational-style responses to questions or inputs, is increasingly being used by both patients and he...

Extracting cancer concepts from clinical notes using natural language processing: a systematic review.

BMC bioinformatics
BACKGROUND: Extracting information from free texts using natural language processing (NLP) can save time and reduce the hassle of manually extracting large quantities of data from incredibly complex clinical notes of cancer patients. This study aimed...

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...