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Data Mining

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Leveraging LLMs to Understand Narratives in MAUDE Reports.

Studies in health technology and informatics
Interest in using the MAUDE database to investigate adverse events linked to medical devices has been growing. Yet, the narrative sections of these reports remain largely unexplored, leaving valuable insights unutilized and creating an incomplete und...

GPT-4 in Clinical Practice: Assessing Its Capability for Symptom Extraction from Cancer Patient Notes.

Studies in health technology and informatics
Accurate extraction of patient symptoms and signs from clinical notes is essential for effective diagnosis, treatment planning, and research. In this study, we evaluate the capability of GPT-4, specifically GPT-4o, in extracting symptoms and signs fr...

Evaluation of the Performance of a Large Language Model to Extract Signs and Symptoms from Clinical Notes.

Studies in health technology and informatics
Large language models (LLMs) have increasingly been used to extract critical information from unstructured clinical notes, which often include important details not captured in the structured sections of electronic health records (EHRs). This study a...

A knowledge tracing approach with dual graph convolutional networks and positive/negative feature enhancement network.

PloS one
Knowledge tracing models predict students' mastery of specific knowledge points by analyzing their historical learning performance. However, existing methods struggle with handling a large number of skills, data sparsity, learning differences, and co...

Prompting large language models to extract chemical‒disease relation precisely and comprehensively at the document level: an evaluation study.

PloS one
Given the scarcity of annotated data, current deep learning methods face challenges in the field of document-level chemical-disease relation extraction, making it difficult to achieve precise relation extraction capable of identifying relation types ...

MISTIC: a novel approach for metastasis classification in Italian electronic health records using transformers.

BMC medical informatics and decision making
BACKGROUND: Analysis of Electronic Health Records (EHRs) is crucial in real-world evidence (RWE), especially in oncology, as it provides valuable insights into the complex nature of the disease. The implementation of advanced techniques for automated...

Improving Phenotyping of Patients With Immune-Mediated Inflammatory Diseases Through Automated Processing of Discharge Summaries: Multicenter Cohort Study.

JMIR medical informatics
BACKGROUND: Valuable insights gathered by clinicians during their inquiries and documented in textual reports are often unavailable in the structured data recorded in electronic health records (EHRs).

Applying Data Mining to Predict Perceived Benefits Risks of Robotics at Home for Dementia Caregiving Among African American Families.

Studies in health technology and informatics
We used data mining to predict the attitudes of 527 caregivers towards the pros and cons of using robotics and artificial intelligence (AI) for dementia care in African American families, with a focus on family-level factors. African American family ...

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.

JMIR formative research
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...

ESM-Ezy: a deep learning strategy for the mining of novel multicopper oxidases with superior properties.

Nature communications
The UniProt database is a valuable resource for biocatalyst discovery, yet predicting enzymatic functions remains challenging, especially for low-similarity sequences. Identifying superior enzymes with enhanced catalytic properties is even harder. To...