AIMC Topic: Data Mining

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Text mining for identification of biological entities related to antibiotic resistant organisms.

PeerJ
Antimicrobial resistance is a significant public health problem worldwide. In recent years, the scientific community has been intensifying efforts to combat this problem; many experiments have been developed, and many articles are published in this a...

Microbial Dark Matter: from Discovery to Applications.

Genomics, proteomics & bioinformatics
With the rapid increase of the microbiome samples and sequencing data, more and more knowledge about microbial communities has been gained. However, there is still much more to learn about microbial communities, including billions of novel species an...

Multilabel classification of medical concepts for patient clinical profile identification.

Artificial intelligence in medicine
BACKGROUND: The development of electronic health records has provided a large volume of unstructured biomedical information. Extracting patient characteristics from these data has become a major challenge, especially in languages other than English.

Prototype Regularized Manifold Regularization Technique for Semi-Supervised Online Extreme Learning Machine.

Sensors (Basel, Switzerland)
Data streaming applications such as the Internet of Things (IoT) require processing or predicting from sequential data from various sensors. However, most of the data are unlabeled, making applying fully supervised learning algorithms impossible. The...

Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review.

Sensors (Basel, Switzerland)
Road condition monitoring (RCM) has been a demanding strategic research area in maintaining a large network of transport infrastructures. With advancements in computer vision and data mining techniques along with high computing resources, several inn...

A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting.

Computational intelligence and neuroscience
The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the...

Optimization-Based Ensemble Feature Selection Algorithm and Deep Learning Classifier for Parkinson's Disease.

Journal of healthcare engineering
PD (Parkinson's Disease) is a severe malady that is painful and incurable, affecting older human beings. Identifying PD early in a precise manner is critical for the lengthened survival of patients, where DMTs (data mining techniques) and MLTs (machi...

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

Computational intelligence and neuroscience
It was to explore the application value of health cloud service platform based on data mining algorithm and wireless network in the analysis of psychosocial factors and psychological characteristics of personality of patients with chronic diseases. B...

Clustering at the Disposal of Industry 4.0: Automatic Extraction of Plant Behaviors.

Sensors (Basel, Switzerland)
For two centuries, the industrial sector has never stopped evolving. Since the dawn of the Fourth Industrial Revolution, commonly known as Industry 4.0, deep and accurate understandings of systems have become essential for real-time monitoring, predi...

E-Commerce Information System Management Based on Data Mining and Neural Network Algorithms.

Computational intelligence and neuroscience
The rapid development of artificial intelligence technology has led to rapid development in various fields. It has many hidden related customer behavior information and future development trends in the e-commerce information system. The data mining t...