AIMC Topic: Machine Learning

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Data Analysis and Knowledge Mining of Machine Learning in Soil Corrosion Factors of the Pipeline Safety.

Computational intelligence and neuroscience
The purpose of this research is to enhance the ability of data analysis and knowledge mining in soil corrosion factors of the pipeline. According to its multifactor characteristics, the rough set algorithm is directly used to analyze and process the ...

Modern Learning from Big Data in Critical Care: Primum Non Nocere.

Neurocritical care
Large and complex data sets are increasingly available for research in critical care. To analyze these data, researchers use techniques commonly referred to as statistical learning or machine learning (ML). The latter is known for large successes in ...

Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review.

Computers in biology and medicine
Being a second most cause of mortality worldwide, cancer has been identified as a perilous disease for human beings, where advance stage diagnosis may not help much in safeguarding patients from mortality. Thus, efforts to provide a sustainable archi...

Joint Feature Synthesis and Embedding: Adversarial Cross-Modal Retrieval Revisited.

IEEE transactions on pattern analysis and machine intelligence
Recently, generative adversarial network (GAN) has shown its strong ability on modeling data distribution via adversarial learning. Cross-modal GAN, which attempts to utilize the power of GAN to model the cross-modal joint distribution and to learn c...

Geometry-Aware Generation of Adversarial Point Clouds.

IEEE transactions on pattern analysis and machine intelligence
Machine learning models have been shown to be vulnerable to adversarial examples. While most of the existing methods for adversarial attack and defense work on the 2D image domain, a few recent attempts have been made to extend them to 3D point cloud...

Ensuring the Reliability of Virtual Sensors Based on Artificial Intelligence within Vehicle Dynamics Control Systems.

Sensors (Basel, Switzerland)
The use of virtual sensors in vehicles represents a cost-effective alternative to the installation of physical hardware. In addition to physical models resulting from theoretical modeling, artificial intelligence and machine learning approaches are i...

Evaluation of Machine Learning Models for Clinical Prediction Problems.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

Dynamic Mortality Risk Predictions for Children in ICUs: Development and Validation of Machine Learning Models.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVES: Assess a machine learning method of serially updated mortality risk.

Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning.

Computational intelligence and neuroscience
A key challenge in clinical recommendation systems is the problem of aberrant patient profiles in social networks. As a result of a person's abnormal profile, numerous vests might be used to make fake remarks about them, cyber bullying, or cyber-atta...

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...