AI Medical Compendium Topic:
Data Mining

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Application of machine learning in rheumatic disease research.

The Korean journal of internal medicine
Over the past decade, there has been a paradigm shift in how clinical data are collected, processed and utilized. Machine learning and artificial intelligence, fueled by breakthroughs in high-performance computing, data availability and algorithmic i...

Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

Medical physics
PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., random forests) and single-model methods (e.g., logistic regression and decision trees) in predictive modeling of post-RT treatment failure and adverse eve...

The analysis of the effects of acute rheumatic fever in childhood on cardiac disease with data mining.

International journal of medical informatics
BACKGROUND: Acute rheumatic fever (ARF) is an important disease that is frequently seen in Turkey, it is necessary to develop solutions to cure the disease. It is believed that new data analysis methods may be applied to this disease, and this may be...

Particle swarm optimization for network-based data classification.

Neural networks : the official journal of the International Neural Network Society
Complex networks provide a powerful tool for data representation due to its ability to describe the interplay between topological, functional, and dynamical properties of the input data. A fundamental process in network-based (graph-based) data analy...

Use of natural language processing in electronic medical records to identify pregnant women with suicidal behavior: towards a solution to the complex classification problem.

European journal of epidemiology
We developed algorithms to identify pregnant women with suicidal behavior using information extracted from clinical notes by natural language processing (NLP) in electronic medical records. Using both codified data and NLP applied to unstructured cli...

Application of data mining methods to improve screening for the risk of early gastric cancer.

BMC medical informatics and decision making
BACKGROUND: Although gastric cancer is a malignancy with high morbidity and mortality in China, the survival rate of patients with early gastric cancer (EGC) is high after surgical resection. To strengthen diagnosing and screening is the key to impro...

SBLC: a hybrid model for disease named entity recognition based on semantic bidirectional LSTMs and conditional random fields.

BMC medical informatics and decision making
BACKGROUND: Disease named entity recognition (NER) is a fundamental step in information processing of medical texts. However, disease NER involves complex issues such as descriptive modifiers in actual practice. The accurate identification of disease...

Clinical text annotation - what factors are associated with the cost of time?

AMIA ... Annual Symposium proceedings. AMIA Symposium
Building high-quality annotated clinical corpora is necessary for developing statistical Natural Language Processing (NLP) models to unlock information embedded in clinical text, but it is also time consuming and expensive. Consequently, it important...

Mining Disease-Symptom Relation from Massive Biomedical Literature and Its Application in Severe Disease Diagnosis.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Disease-symptom relation is an important biomedical relation that can be used for clinical decision support including building medical diagnostic systems. Here we present a study on mining disease-symptom relation from massive biomedical literature a...

A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature.

AMIA ... Annual Symposium proceedings. AMIA Symposium
As the cost of DNA sequencing continues to fall, an increasing amount of information on human genetic variation is being produced that could help progress precision medicine. However, information about such mutations is typically first made available...