AI Medical Compendium Topic

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Data Mining

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The influence of prompt engineering on large language models for protein-protein interaction identification in biomedical literature.

Scientific reports
Identifying protein-protein interactions (PPIs) is a foundational task in biomedical natural language processing. While specialized models have been developed, the potential of general-domain large language models (LLMs) in PPI extraction, particular...

Rapid Adaptation of Chemical Named Entity Recognition Using Few-Shot Learning and LLM Distillation.

Journal of chemical information and modeling
Named entity recognition (NER) has been widely used in chemical text mining for the automatic identification and extraction of chemical entities. However, existing chemical NER systems primarily focus on scenarios with abundant training data, requiri...

Enhancing medical text classification with GAN-based data augmentation and multi-task learning in BERT.

Scientific reports
With the rapid advancement of medical informatics, the accumulation of electronic medical records and clinical diagnostic data provides unprecedented opportunities for intelligent medical text classification. However, challenges such as class imbalan...

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.

A sustainable system for predicting appliance energy consumption based on machine learning.

Journal of environmental management
Nowadays, energy conservation is a top priority for sustainable societies, which focus on environmental and economic sustainability to address fossil fuel scarcity, climate change, and increasing environmental pollution. Therefore, planning for energ...

101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

International journal of molecular sciences
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the digestive tract, characterized by a high recurrence rate and inadequate immunotherapy options. We analyzed mutation data of ESCC from public databases and...

Privacy-preserving federated learning for collaborative medical data mining in multi-institutional settings.

Scientific reports
Ensuring data privacy in medical image classification is a critical challenge in healthcare, especially with the increasing reliance on AI-driven diagnostics. In fact, over 30% of healthcare organizations globally have experienced a data breach in th...

End-to-end Chinese clinical event extraction based on large language model.

Scientific reports
Clinical event extraction is crucial for structuring medical data, supporting clinical decision-making, and enabling other intelligent healthcare services. Traditional approaches for clinical event extraction often use pipeline-based methods to ident...

Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models.

JMIR medical informatics
BACKGROUND: Research on chronic multimorbidity has increasingly become a focal point with the aging of the population. Many studies in this area require detailed patient characteristic information. However, the current methods for extracting such inf...

Adaptive mechanism-based grey wolf optimizer for feature selection in high-dimensional classification.

PloS one
Feature Selection (FS) is a crucial component of machine learning and data mining. Its goal is to eliminate redundant and irrelevant features from a datasets, thereby enhancing the classifier's performance. The Grey Wolf Optimizer (GWO) is a well-kno...