AIMC Topic: Machine Learning

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The role of artificial intelligence in paediatric neuroradiology.

Pediatric radiology
Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping...

A morphometric analysis of the osteocyte canaliculus using applied automatic semantic segmentation by machine learning.

Journal of bone and mineral metabolism
INTRODUCTION: Osteocytes play a role as mechanosensory cells by sensing flow-induced mechanical stimuli applied on their cell processes. High-resolution imaging of osteocyte processes and the canalicular wall are necessary for the analysis of this me...

Explaining spatial accessibility to high-quality nursing home care in the US using machine learning.

Spatial and spatio-temporal epidemiology
In this study we measure and map the system-wide spatial accessibility to good quality nursing home care for all counties in the contiguous United States, and use an 'imputed post-lasso' machine learning technique to systematically examine this acces...

Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review.

Sensors (Basel, Switzerland)
Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be allocated to fault-prone modules...

A Machine Learning Model for Early Prediction and Detection of Sepsis in Intensive Care Unit Patients.

Journal of healthcare engineering
In today's scenario, sepsis is impacting millions of patients in the intensive care unit due to the fact that the mortality rate is increased exponentially and has become a major challenge in the field of healthcare. Such peoples require determinant ...

China's Economic Forecast Based on Machine Learning and Quantitative Easing.

Computational intelligence and neuroscience
In this paper, six variables, including export value, real exchange rate, Chinese GDP, and US IPI, and their seasonal variables, are used as determinants to model and forecast China's export value to the US using three methods: BP neural network, ARI...

A Novel and Effective Brain Tumor Classification Model Using Deep Feature Fusion and Famous Machine Learning Classifiers.

Computational intelligence and neuroscience
Brain tumors are difficult to treat and cause substantial fatalities worldwide. Medical professionals visually analyze the images and mark out the tumor regions to identify brain tumors, which is time-consuming and prone to error. Researchers have pr...

Regression trees and ensembles for cumulative incidence functions.

The international journal of biostatistics
The use of cumulative incidence functions for characterizing the risk of one type of event in the presence of others has become increasingly popular over the past two decades. The problems of modeling, estimation and inference have been treated using...

IoT and AI-Based Application for Automatic Interpretation of the Affective State of Children Diagnosed with Autism.

Sensors (Basel, Switzerland)
In the context in which it was demonstrated that humanoid robots are efficient in helping children diagnosed with autism in exploring their affective state, this paper underlines and proves the efficiency of a previously developed machine learning-ba...

An On-Device Learning System for Estimating Liquid Consumption from Consumer-Grade Water Bottles and Its Evaluation.

Sensors (Basel, Switzerland)
A lightweight on-device liquid consumption estimation system involving an energy-aware machine learning algorithm is developed in this work. This system consists of two separate on-device neural network models that carry out liquid consumption estima...