AIMC Topic:
Data Mining

Clear Filters Showing 1211 to 1220 of 1549 articles

Optimizing Data Extraction: Harnessing RAG and LLMs for German Medical Documents.

Studies in health technology and informatics
In the field of medical data analysis, converting unstructured text documents into a structured format suitable for further use is a significant challenge. This study introduces an automated local deployed data privacy secure pipeline that uses open-...

Unveiling Medical Insights: Advanced Topic Extraction from Scientific Articles.

Studies in health technology and informatics
In the ever-evolving landscape of medical research and healthcare, the abundance of scientific articles presents both a treasure trove of knowledge and a daunting challenge. Researchers, clinicians, and data scientists grapple with vast amounts of un...

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...

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...

Leveraging Rule-Based NLP to Translate Textual Reports as Structured Inputs Automatically Processed by a Clinical Decision Support System.

Studies in health technology and informatics
Using clinical decision support systems (CDSSs) for breast cancer management necessitates to extract relevant patient data from textual reports which is a complex task although efficiently achieved by machine learning but black box methods. We propos...

Assessment of Follow-Up for Pulmonary Nodules from Radiology Reports with Natural Language Processing.

Studies in health technology and informatics
Radiology reports are an essential communication method for ensuring smooth workflow in healthcare. However, many of these reports are described in free text, and findings documented by radiologists may not be adequately addressed. In this study, foc...

Unsupervised Extraction of Body-Text from Clinical PDF Documents.

Studies in health technology and informatics
Automatic extraction of body-text within clinical PDF documents is necessary to enhance downstream NLP tasks but remains a challenge. This study presents an unsupervised algorithm designed to extract body-text leveraging large volume of data. Using D...

Automatic Extraction of Medication Data from Semi-Structured Prescriptions.

Studies in health technology and informatics
In many healthcare facilities, the prescription of drugs is done only in a semi-structured manner, using free-text fields where various information is often mixed. Therefore, automatic processing, especially for secondary use such as research purpose...

Temporal Characterization and Visualization of Revolving Therapy-Events in Lung Cancer Patients.

Studies in health technology and informatics
This paper presents a comprehensive workflow for integrating revolving events into the transitive sequential pattern mining (tSPM+) algorithm and Machine Learning for Health Outcomes (MLHO) framework, emphasizing best practices and pitfalls in its ap...