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Data Mining

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Text mining of verbal autopsy narratives to extract mortality causes and most prevalent diseases using natural language processing.

PloS one
Verbal autopsy (VA) narratives play a crucial role in understanding and documenting the causes of mortality, especially in regions lacking robust medical infrastructure. In this study, we propose a comprehensive approach to extract mortality causes a...

Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

AJR. American journal of roentgenology
Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligenc...

Development of message passing-based graph convolutional networks for classifying cancer pathology reports.

BMC medical informatics and decision making
BACKGROUND: Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language...

Utility analysis and demonstration of real-world clinical texts: A case study on Japanese cancer-related EHRs.

PloS one
Real-world data (RWD) in the medical field, such as electronic health records (EHRs) and medication orders, are receiving increasing attention from researchers and practitioners. While structured data have played a vital role thus far, unstructured d...

Community knowledge graph abstraction for enhanced link prediction: A study on PubMed knowledge graph.

Journal of biomedical informatics
OBJECTIVE: As new knowledge is produced at a rapid pace in the biomedical field, existing biomedical Knowledge Graphs (KGs) cannot be manually updated in a timely manner. Previous work in Natural Language Processing (NLP) has leveraged link predictio...

The Potential of Gemini and GPTs for Structured Report Generation based on Free-Text F-FDG PET/CT Breast Cancer Reports.

Academic radiology
RATIONALE AND OBJECTIVE: To compare the performance of large language model (LLM) based Gemini and Generative Pre-trained Transformers (GPTs) in data mining and generating structured reports based on free-text PET/CT reports for breast cancer after u...

Biomedical event causal relation extraction with deep knowledge fusion and Roberta-based data augmentation.

Methods (San Diego, Calif.)
Biomedical event causal relation extraction (BECRE), as a subtask of biomedical information extraction, aims to extract event causal relation facts from unstructured biomedical texts and plays an essential role in many downstream tasks. The existing ...

Prediction of infectious diseases using sentiment analysis on social media data.

PloS one
As the influence and risk of infectious diseases increase, efforts are being made to predict the number of confirmed infectious disease patients, but research involving the qualitative opinions of social media users is scarce. However, social data ca...

A machine learning framework for extracting information from biological pathway images in the literature.

Metabolic engineering
There have been significant advances in literature mining, allowing for the extraction of target information from the literature. However, biological literature often includes biological pathway images that are difficult to extract in an easily edita...