AI Medical Compendium Topic

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Data Mining

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Deep semi-supervised learning ensemble framework for classifying co-mentions of human proteins and phenotypes.

BMC bioinformatics
BACKGROUND: Identifying human protein-phenotype relationships has attracted researchers in bioinformatics and biomedical natural language processing due to its importance in uncovering rare and complex diseases. Since experimental validation of prote...

Chinese Language Feature Analysis Based on Multilayer Self-Organizing Neural Network and Data Mining Techniques.

Computational intelligence and neuroscience
As one of the oldest languages in the world, Chinese has a long cultural history and unique language charm. The multilayer self-organizing neural network and data mining techniques have been widely used and can achieve high-precision prediction in di...

A practical approach towards causality mining in clinical text using active transfer learning.

Journal of biomedical informatics
OBJECTIVE: Causality mining is an active research area, which requires the application of state-of-the-art natural language processing techniques. In the healthcare domain, medical experts create clinical text to overcome the limitation of well-defin...

SicknessMiner: a deep-learning-driven text-mining tool to abridge disease-disease associations.

BMC bioinformatics
BACKGROUND: Blood cancers (BCs) are responsible for over 720 K yearly deaths worldwide. Their prevalence and mortality-rate uphold the relevance of research related to BCs. Despite the availability of different resources establishing Disease-Disease ...

SCMAG: A Semisupervised Single-Cell Clustering Method Based on Matrix Aggregation Graph Convolutional Neural Network.

Computational and mathematical methods in medicine
Clustering analysis is one of the most important technologies for single-cell data mining. It is widely used in the division of different gene sequences, the identification of functional genes, and the detection of new cell types. Although the tradit...

Feature Selection and Feature Stability Measurement Method for High-Dimensional Small Sample Data Based on Big Data Technology.

Computational intelligence and neuroscience
With the rapid development of artificial intelligence in recent years, the research on image processing, text mining, and genome informatics has gradually deepened, and the mining of large-scale databases has begun to receive more and more attention....

Sports Training System Based on Convolutional Neural Networks and Data Mining.

Computational intelligence and neuroscience
In recent years, China's sports industry has achieved good development, but the efficiency of athletes in the training process is difficult to have scientific guarantee. How to use scientific algorithm and data mining technology to accurately guide t...

Machine Learning Applications in Solid Organ Transplantation and Related Complications.

Frontiers in immunology
The complexity of transplant medicine pushes the boundaries of innate, human reasoning. From networks of immune modulators to dynamic pharmacokinetics to variable postoperative graft survival to equitable allocation of scarce organs, machine learning...

Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.

Orthodontics & craniofacial research
Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning underlying biomedicine. Complexity theory, Network analysis and Artificial Intelligence are already appro...

Marketable value estimation of patents using ensemble learning methodology: Focusing on U.S. patents for the electricity sector.

PloS one
Patent valuation is required to revitalize patent transactions, but calculating a reasonable value that consumers and suppliers could satisfy is difficult. When machine learning is used, a quantitative evaluation based on a large volume of data is po...