AIMC Topic: Algorithms

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Age-specific risk factors for the prediction of obesity using a machine learning approach.

Frontiers in public health
Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely complex topic, involving biological, physiological, psychological, and environmental factors. One suc...

Personalized online ensemble machine learning with applications for dynamic data streams.

Statistics in medicine
In this work we introduce the personalized online super learner (POSL), an online personalizable ensemble machine learning algorithm for streaming data. POSL optimizes predictions with respect to baseline covariates, so personalization can vary from ...

Improved Bidirectional RRT* Algorithm for Robot Path Planning.

Sensors (Basel, Switzerland)
In order to address the shortcomings of the traditional bidirectional RRT* algorithm, such as its high degree of randomness, low search efficiency, and the many inflection points in the planned path, we institute improvements in the following directi...

DCP-SLAM: Distributed Collaborative Partial Swarm SLAM for Efficient Navigation of Autonomous Robots.

Sensors (Basel, Switzerland)
Collaborative robots represent an evolution in the field of swarm robotics that is pervasive in modern industrial undertakings from manufacturing to exploration. Though there has been much work on path planning for autonomous robots employing floor p...

Low Cost Magnetic Field Control for Disabled People.

Sensors (Basel, Switzerland)
Our research presents a cost-effective navigation system for electric wheelchairs that utilizes the tongue as a human-machine interface (HMI) for disabled individuals. The user controls the movement of the wheelchair by wearing a small neodymium magn...

Comparison of Artificial Neural Network and Polynomial Approximation Models for Reflectance Spectra Reconstruction.

Sensors (Basel, Switzerland)
Knowledge of surface reflection of an object is essential in many technological fields, including graphics and cultural heritage. Compared to direct multi- or hyper-spectral capturing approaches, commercial RGB cameras allow for a high resolution and...

A Combined Region- and Pixel-Based Deep Learning Approach for Quantifying Abdominal Adipose Tissue in Adolescents Using Dixon Magnetic Resonance Imaging.

Tomography (Ann Arbor, Mich.)
BACKGROUND: The development of adipose tissue during adolescence may provide valuable insights into obesity-associated diseases. We propose an automated convolutional neural network (CNN) approach using Dixon-based magnetic resonance imaging (MRI) to...

Point Cloud Deep Learning Network Based on Balanced Sampling and Hybrid Pooling.

Sensors (Basel, Switzerland)
The automatic semantic segmentation of point cloud data is important for applications in the fields of machine vision, virtual reality, and smart cities. The processing capability of the point cloud segmentation method with PointNet++ as the baseline...

Machine learning toward high-performance electrochemical sensors.

Analytical and bioanalytical chemistry
The so-coined fourth paradigm in science has reached the sensing area, with the use of machine learning (ML) toward data-driven improvements in sensitivity, reproducibility, and accuracy, along with the determination of multiple targets from a single...

Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Celiac disease with its endoscopic manifestation of villous atrophy (VA) is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of VA at routine EGD may improve diagnostic perfo...