AIMC Topic: Data Mining

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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...

Automatically disambiguating medical acronyms with ontology-aware deep learning.

Nature communications
Modern machine learning (ML) technologies have great promise for automating diverse clinical and research workflows; however, training them requires extensive hand-labelled datasets. Disambiguating abbreviations is important for automated clinical no...

Literature Mining and Mechanistic Graphical Modelling to Improve mRNA Vaccine Platforms.

Frontiers in immunology
RNA vaccines represent a milestone in the history of vaccinology. They provide several advantages over more traditional approaches to vaccine development, showing strong immunogenicity and an overall favorable safety profile. While preclinical testin...

Predicting affinity ties in a surname network.

PloS one
From administrative registers of last names in Santiago, Chile, we create a surname affinity network that encodes socioeconomic data. This network is a multi-relational graph with nodes representing surnames and edges representing the prevalence of i...

Difference Analysis of Regional Economic Development Based on the SOM Neural Network with the Hybrid Genetic Algorithm.

Computational intelligence and neuroscience
Since the reform and opening up, China's regional economy has developed rapidly. However, due to different starting points of economic development caused by the traditional distribution of productive forces and the differences in regions, resources, ...