AIMC Topic: Data Mining

Clear Filters Showing 1271 to 1280 of 1626 articles

Techniques for learning and transferring knowledge for microbiome-based classification and prediction: review and assessment.

Briefings in bioinformatics
The volume of microbiome data is growing at an exponential rate, and the current methodologies for big data mining are encountering substantial obstacles. Effectively managing and extracting valuable insights from these vast microbiome datasets has e...

Utilizing RAG and GPT-4 for Extraction of Substance Use Information from Clinical Notes.

Studies in health technology and informatics
This research investigates the application of a hybrid Retrieval-Augmented Generation (RAG) and Generative Pre-trained Transformer (GPT) pipeline for extracting and categorizing substance use information from unstructured clinical notes. The aim is t...

[Construction and external validation of a non-invasive pre-hospital screening model for stroke patients: a study based on artificial intelligence DeepFM algorithm].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their famil...

CACER: Clinical concept Annotations for Cancer Events and Relations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symptom burden...

Automated annotation of scientific texts for ML-based keyphrase extraction and validation.

Database : the journal of biological databases and curation
Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant c...

[Progress in application of machine learning in epidemiology].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi
Population based health data collection and analysis are important in epidemiological research. In recent years, with the rapid development of big data, Internet and cloud computing, artificial intelligence has gradually attracted attention of epidem...

Improving dictionary-based named entity recognition with deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Dictionary-based named entity recognition (NER) allows terms to be detected in a corpus and normalized to biomedical databases and ontologies. However, adaptation to different entity types requires new high-quality dictionaries and associ...

LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To investigate the demonstration in large language models (LLMs) for biomedical relation extraction. This study introduces a framework comprising three types of adaptive tuning methods to assess their impacts and effectiveness.

Ensemble pretrained language models to extract biomedical knowledge from literature.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: The rapid expansion of biomedical literature necessitates automated techniques to discern relationships between biomedical concepts from extensive free text. Such techniques facilitate the development of detailed knowledge bases and highl...

Taiyi: a bilingual fine-tuned large language model for diverse biomedical tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Most existing fine-tuned biomedical large language models (LLMs) focus on enhancing performance in monolingual biomedical question answering and conversation tasks. To investigate the effectiveness of the fine-tuned LLMs on diverse biomedi...