AIMC Topic: Natural Language Processing

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Bridging Gaps with Generative AI: Enhancing Hypertension Monitoring Through Patient and Provider Insights.

Studies in health technology and informatics
This study introduces a Generative Artificial Intelligence (GenAI) assistant designed to address key challenges in Remote Patient Monitoring (RPM) for hypertension. After a comprehensive needs assessment from clinicians and patients, we identified pi...

A Comprehensive Natural Language Processing Pipeline for the Chronic Lupus Disease.

Studies in health technology and informatics
Electronic Health Records (EHRs) contain a wealth of unstructured patient data, making it challenging for physicians to do informed decisions. In this paper, we introduce a Natural Language Processing (NLP) approach for the extraction of therapies, d...

Exploring Offline Large Language Models for Clinical Information Extraction: A Study of Renal Histopathological Reports of Lupus Nephritis Patients.

Studies in health technology and informatics
Open source, lightweight and offline generative large language models (LLMs) hold promise for clinical information extraction due to their suitability to operate in secured environments using commodity hardware without token cost. By creating a simpl...

Accelerating Clinical Text Annotation in Underrepresented Languages: A Case Study on Text De-Identification.

Studies in health technology and informatics
Clinical notes contain valuable information for research and monitoring quality of care. Named Entity Recognition (NER) is the process for identifying relevant pieces of information such as diagnoses, treatments, side effects, etc., and bring them to...

Exploring Explainable AI Techniques for Text Classification in Healthcare: A Scoping Review.

Studies in health technology and informatics
Text classification plays an essential role in the medical domain by organizing and categorizing vast amounts of textual data through machine learning (ML) and deep learning (DL). The adoption of Artificial Intelligence (AI) technologies in healthcar...

Comparative Evaluation of Pre-Trained Language Models for Biomedical Information Retrieval.

Studies in health technology and informatics
Finding relevant information in the biomedical literature increasingly depends on efficient information retrieval (IR) algorithms. Cross-Encoders, SentenceBERT, and ColBERT are algorithms based on pre-trained language models that use nuanced but comp...

Comparing a Large Language Model with Previous Deep Learning Models on Named Entity Recognition of Adverse Drug Events.

Studies in health technology and informatics
The ability to fine-tune pre-trained deep learning models to learn how to process a downstream task using a large training set allow to significantly improve performances of named entity recognition. Large language models are recent models based on t...

Enhancing Clinical Data Extraction from Pathology Reports: A Comparative Analysis of Large Language Models.

Studies in health technology and informatics
This study evaluates the efficacy of a small large language model (sLLM) in extracting critical information from free-text pathology reports across multiple centers, addressing the challenges posed by the narrative and complex nature of these documen...

Unlocking the Potential of Free Text in Electronic Health Records with Large Language Models (LLM): Enhancing Patient Safety and Consultation Interactions.

Studies in health technology and informatics
Computer-mediated clinical consultation, involving clinicians, electronic health record (EHR) systems, and patients, yield rich narrative data. Despite advancements in Natural Language Processing (NLP), these narratives remain underutilised. Free tex...

Pre-Processing of Categorical Features Within Medical Analysis Systems.

Studies in health technology and informatics
The complexity of the cancer problem domain presents challenges not only to the medical analysis systems tasked with its analysis, but also to the users of such systems. While it is desirable to assist users in operating these medical analysis system...