AIMC Topic: Machine Learning

Clear Filters Showing 17521 to 17530 of 34417 articles

A Continuous Learning Approach for Real-Time Network Intrusion Detection.

International journal of neural systems
Network intrusion detection is becoming a challenging task with cyberattacks that are becoming more and more sophisticated. Failing the prevention or detection of such intrusions might have serious consequences. Machine learning approaches try to rec...

Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data.

Computational and mathematical methods in medicine
The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic ...

[Artificial intelligence and medical imaging].

Bulletin du cancer
The use of artificial intelligence methods for image recognition is one of the most developed branches of the AI field and these technologies are now commonly used in our daily lives. In the field of medical imaging, approaches based on artificial in...

Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations.

NeuroImage
In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now strong evidence that somatotopic organization is evident across other regions in the sensorimotor network. This raises several experimental questions: To ...

Event Detection for Distributed Acoustic Sensing: Combining Knowledge-Based, Classical Machine Learning, and Deep Learning Approaches.

Sensors (Basel, Switzerland)
Distributed Acoustic Sensing (DAS) is a promising new technology for pipeline monitoring and protection. However, a big challenge is distinguishing between relevant events, like intrusion by an excavator near the pipeline, and interference, like land...

An Empirical Study of Training Data Selection Methods for Ranking-Oriented Cross-Project Defect Prediction.

Sensors (Basel, Switzerland)
Ranking-oriented cross-project defect prediction (ROCPDP), which ranks software modules of a new target industrial project based on the predicted defect number or density, has been suggested in the literature. A major concern of ROCPDP is the distrib...

Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications.

Sensors (Basel, Switzerland)
The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a ...

Emulating complex simulations by machine learning methods.

BMC bioinformatics
BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and ...

Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway.

PloS one
Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and utility as biomarkers remains poorly understood. In this study, we analysed 505 PTC patients by employ...

Detecting fine and elaborate movements with piezo sensors provides non-invasive access to overlooked behavioral components.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Behavioral phenotyping devices have been successfully used to build ethograms, but many aspects of behavior remain out of reach of available phenotyping systems. We now report on a novel device, which consists in an open-field platform resting on hig...