AIMC Topic: Natural Language Processing

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Using Large Language Models for Advanced and Flexible Labelling of Protocol Deviations in Clinical Development.

Therapeutic innovation & regulatory science
BACKGROUND: As described in ICH E3 Q&A R1 (International Council for Harmonisation. E3: Structure and content of clinical study reports-questions and answers (R1). 6 July 2012. Available from: https://database.ich.org/sites/default/files/E3_Q%26As_R1...

Learning Emotion Category Representation to Detect Emotion Relations Across Languages.

IEEE transactions on pattern analysis and machine intelligence
Understanding human emotions is crucial for a myriad of applications, from psychological research to advancements in Natural Language Processing (NLP). Traditionally, emotions are categorized into distinct basic groups, which has led to the developme...

Learning a deep language model for microbiomes: The power of large scale unlabeled microbiome data.

PLoS computational biology
We use open source human gut microbiome data to learn a microbial "language" model by adapting techniques from Natural Language Processing (NLP). Our microbial "language" model is trained in a self-supervised fashion (i.e., without additional externa...

Sentences, entities, and keyphrases extraction from consumer health forums using multi-task learning.

Journal of biomedical semantics
PURPOSE: Online consumer health forums offer an alternative source of health-related information for internet users seeking specific details that may not be readily available through articles or other one-way communication channels. However, the effe...

A Dataset of Real and Synthetic Speech in Ukrainian.

Scientific data
This work is dedicated to the analysis and evaluation of the DRSSU dataset: A Dataset of Real and Synthetic Speech in Ukrainian, created to support research in the field of natural language processing and speech recognition. The dataset contains a un...

Assessing autobiographical memory consistency: Machine and human approaches.

Behavior research methods
Memory is far from a stable representation of what we have encountered. Over time, we can forget, modify, and distort the details of our experiences. How autobiographical memory-the memories we have for our personal past-changes has important ramific...

MedFILIP: Medical Fine-Grained Language-Image Pre-Training.

IEEE journal of biomedical and health informatics
Medical vision-language pretraining (VLP) that leverages naturally-paired medical image-report data is crucial for medical image analysis. However, existing methods struggle to accurately characterize associations between images and diseases, leading...

The Applications of Large Language Models in Mental Health: Scoping Review.

Journal of medical Internet research
BACKGROUND: Mental health is emerging as an increasingly prevalent public issue globally. There is an urgent need in mental health for efficient detection methods, effective treatments, affordable privacy-focused health care solutions, and increased ...

Systematic Identification of Caregivers of Patients Living With Dementia in the Electronic Health Record: Known Contacts and Natural Language Processing Cohort Study.

Journal of medical Internet research
BACKGROUND: Systemically identifying caregivers in the electronic health record (EHR) is a critical step for delivering patient-centered care, enhancing care coordination, and advancing research and population health efforts in caregiving. Despite EH...

Identifying emergency department patients at high risk for opioid overdose using natural language processing and machine learning.

Journal of substance use and addiction treatment
INTRODUCTION: Emergency departments (ED) are potential sites for identifying and treating individuals at high risk for opioid overdose. This study used machine learning (ML)-based models to predict opioid overdose death in the 12 months after an ED v...