AIMC Topic: Data Mining

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Natural language processing in drug discovery: bridging the gap between text and therapeutics with artificial intelligence.

Expert opinion on drug discovery
INTRODUCTION: The field of Natural Language Processing (NLP) within the life sciences has exploded in its capacity to aid the extraction and analysis of data from scientific texts in recent years through the advancement of Artificial Intelligence (AI...

Coronary artery disease severity and location detection using deep-mining-based magnetocardiography pattern features.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The objective of this study was to develop an automated, accurate method of assessing coronary artery disease (CAD), including its severity and location, using deep-mining-based magnetocardiography (MCG) pattern features.

Evaluating the effectiveness of biomedical fine-tuning for large language models on clinical tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Large language models (LLMs) have shown potential in biomedical applications, leading to efforts to fine-tune them on domain-specific data. However, the effectiveness of this approach remains unclear. This study aims to critically evaluat...

DiMB-RE: mining the scientific literature for diet-microbiome associations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To develop a corpus annotated for diet-microbiome associations from the biomedical literature and train natural language processing (NLP) models to identify these associations, thereby improving the understanding of their role in health a...

Text mining for case report articles on "peritoneal dialysis" from PubMed database.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy
INTRODUCTION: The number of published medical articles on peritoneal dialysis (PD) has been increasing, and efficiently selecting information from numerous articles can be difficult. In this study, we examined whether artificial intelligence (AI) tex...

Optimized Drug-Drug Interaction Extraction With BioGPT and Focal Loss-Based Attention.

IEEE journal of biomedical and health informatics
Drug-drug interactions (DDIs) are a significant focus in biomedical research and clinical practice due to their potential to compromise treatment outcomes or cause adverse effects. While deep learning approaches have advanced DDI extraction, challeng...

Semi-Supervised PARAFAC2 Decomposition for Computational Phenotyping Using Electronic Health Records.

IEEE journal of biomedical and health informatics
Computational phenotyping uses data mining methods to extract clusters of clinical descriptors, known as phenotypes, from electronic health records (EHR). Tensor factorization methods are very effective in extracting meaningful patterns and have beco...

SNER: Semi-Supervised Named Entity Recognition for Large Volume of Diabetes Data.

IEEE journal of biomedical and health informatics
The medical literature and records on diabetes provide crucial resources for diabetes prevention and treatment. However, extracting entities from these textual diabetes data is crucial but challenging. Named entity recognition (NER) - an important co...

Monitoring patient pathways at a secondary healthcare services through process mining via Fuzzy Miner.

BMC medical informatics and decision making
BACKGROUND: This study explored workflow pathways followed by patients seeking secondary healthcare services at a local hospital in a rural part of Turkey using process mining to improve hospital resource management.

Enhancing biomedical relation extraction through data-centric and preprocessing-robust ensemble learning approach.

Database : the journal of biological databases and curation
The paper describes our biomedical relation extraction system, which is designed to participate in the BioCreative VIII challenge Track 1: BioRED Track, which emphasizes the relation extraction from biomedical literature. Our system employs an ensemb...