AIMC Topic: Data Mining
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Improving entity recognition using ensembles of deep learning and fine-tuned large language models: A case study on adverse event extraction from VAERS and social media.
Journal of biomedical informatics
Feb 7, 2025
OBJECTIVE: Adverse event (AE) extraction following COVID-19 vaccines from text data is crucial for monitoring and analyzing the safety profiles of immunizations, identifying potential risks and ensuring the safe use of these products. Traditional dee...
Information Extraction from Clinical Texts with Generative Pre-trained Transformer Models.
International journal of medical sciences
Feb 3, 2025
Processing and analyzing clinical texts are challenging due to its unstructured nature. This study compared the performance of GPT (Generative Pre-trained Transformer)-3.5 and GPT-4 for extracting information from clinical text. Three types of clin...
Biomedical named entity recognition using improved green anaconda-assisted Bi-GRU-based hierarchical ResNet model.
BMC bioinformatics
Jan 30, 2025
BACKGROUND: Biomedical text mining is a technique that extracts essential information from scientific articles using named entity recognition (NER). Traditional NER methods rely on dictionaries, rules, or curated corpora, which may not always be acce...
Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing.
Parasites & vectors
Jan 29, 2025
BACKGROUND: Amebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method in laboratories involves the microscopy of stool samples. Howeve...
Extracting Housing and Food Insecurity Information From Clinical Notes Using cTAKES.
Health services research
Jan 28, 2025
OBJECTIVE: To assess the utility and challenges of using natural language processing (NLP) in electronic health records (EHRs) to ascertain health-related social needs (HRSNs) among older adults.
An Automated Approach for Domain-Specific Knowledge Graph Generation─Graph Measures and Characterization.
Journal of chemical information and modeling
Jan 28, 2025
In 2020, nearly 3 million scientific and engineering papers were published worldwide (White, K. Publications Output: U.S. Trends And International Comparisons). The vastness of the literature that already exists, the increasing rate of appearance of ...
Scalable information extraction from free text electronic health records using large language models.
BMC medical research methodology
Jan 28, 2025
BACKGROUND: A vast amount of potentially useful information such as description of patient symptoms, family, and social history is recorded as free-text notes in electronic health records (EHRs) but is difficult to reliably extract at scale, limiting...
Discontinuous named entities in clinical text: A systematic literature review.
Journal of biomedical informatics
Jan 23, 2025
OBJECTIVE: Extracting named entities from clinical free-text presents unique challenges, particularly when dealing with discontinuous entities-mentions that are separated by unrelated words. Traditional NER methods often struggle to accurately identi...
Large language models for data extraction from unstructured and semi-structured electronic health records: a multiple model performance evaluation.
BMJ health & care informatics
Jan 19, 2025
OBJECTIVES: We aimed to evaluate the performance of multiple large language models (LLMs) in data extraction from unstructured and semi-structured electronic health records.
Extraction and classification of structured data from unstructured hepatobiliary pathology reports using large language models: a feasibility study compared with rules-based natural language processing.
Journal of clinical pathology
Jan 17, 2025
AIMS: Structured reporting in pathology is not universally adopted and extracting elements essential to research often requires expensive and time-intensive manual curation. The accuracy and feasibility of using large language models (LLMs) to extrac...
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