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Data Mining

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Assessing the Heterogeneity of Complaints Related to Tinnitus and Hyperacusis from an Unsupervised Machine Learning Approach: An Exploratory Study.

Audiology & neuro-otology
INTRODUCTION: Subjective tinnitus (ST) and hyperacusis (HA) are common auditory symptoms that may become incapacitating in a subgroup of patients who thereby seek medical advice. Both conditions can result from many different mechanisms, and as a con...

DTranNER: biomedical named entity recognition with deep learning-based label-label transition model.

BMC bioinformatics
BACKGROUND: Biomedical named-entity recognition (BioNER) is widely modeled with conditional random fields (CRF) by regarding it as a sequence labeling problem. The CRF-based methods yield structured outputs of labels by imposing connectivity between ...

Biomedical event extraction with a novel combination strategy based on hybrid deep neural networks.

BMC bioinformatics
BACKGROUND: Biomedical event extraction is a fundamental and in-demand technology that has attracted substantial interest from many researchers. Previous works have heavily relied on manual designed features and external NLP packages in which the fea...

Features spaces and a learning system for structural-temporal data, and their application on a use case of real-time communication network validation data.

PloS one
The service quality and system dependability of real-time communication networks strongly depends on the analysis of monitored data, to identify concrete problems and their causes. Many of these can be described by either their structural or temporal...

A neural network-based joint learning approach for biomedical entity and relation extraction from biomedical literature.

Journal of biomedical informatics
Recently joint modeling methods of entity and relation exhibit more promising results than traditional pipelined methods in general domain. However, they are inappropriate for the biomedical domain due to numerous overlapping relations in biomedical ...

The Emerging Role of Radiomics in COPD and Lung Cancer.

Respiration; international review of thoracic diseases
Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The application of artificial intelligence in medical imaging has transformed medical images into mineab...

Quantitative knowledge presentation models of traditional Chinese medicine (TCM): A review.

Artificial intelligence in medicine
Modern computer technology sheds light on new ways of innovating Traditional Chinese Medicine (TCM). One method that gets increasing attention is the quantitative research method, which makes use of data mining and artificial intelligence technology ...

Application of data mining in a cohort of Italian subjects undergoing myocardial perfusion imaging at an academic medical center.

Computer methods and programs in biomedicine
INTRODUCTION: Coronary artery disease (CAD) is still one of the primary causes of death in the developed countries. Stress single-photon emission computed tomography is used to evaluate myocardial perfusion and ventricular function in patients with s...