AIMC Topic: Machine Learning

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Real-time data analysis in health monitoring systems: A comprehensive systematic literature review.

Journal of biomedical informatics
Health monitoring systems (HMSs) capture physiological measurements through biosensors (sensing), obtain significant properties and measures from the output signal (perceiving), use algorithms for data analysis (reasoning), and trigger warnings or al...

Human Being Detection from UWB NLOS Signals: Accuracy and Generality of Advanced Machine Learning Models.

Sensors (Basel, Switzerland)
This paper studies the problem of detecting human beings in non-line-of-sight (NLOS) conditions using an ultra-wideband radar. We perform an extensive measurement campaign in realistic environments, considering different body orientations, the obstac...

Digital Twins-Based Impact Response Prediction of Prestressed Steel Structure.

Sensors (Basel, Switzerland)
Civil infrastructure O&M requires intelligent monitoring techniques and control methods to ensure safety. Unfortunately, tedious modeling efforts and the rigorous computing requirements of large-scale civil infrastructure have hindered the developmen...

Machine Learning-Based Cry Diagnostic System for Identifying Septic Newborns.

Journal of voice : official journal of the Voice Foundation
BACKGROUND AND OBJECTIVE: Processing the newborns' cry audio signal (CAS) provides valuable information about the newborns' condition. This information can be used to diagnose the disease. This article analyzes the CASs of newborns under two months o...

IoT-based automated water pollution treatment using machine learning classifiers.

Environmental technology
Water is one of the most vital sources for the survival of life. In the globe, the accessibility of water in safe and healthy ways is a major concern. The consumption of unsafe water may lead to health risks. Therefore, it is necessary to classify an...

Machine learning models for accurate prioritization of variants of uncertain significance.

Human mutation
The growing use of next-generation sequencing technologies on genetic diagnosis has produced an exponential increase in the number of variants of uncertain significance (VUS). In this manuscript, we compare three machine learning methods to classify ...

A Predictive Analysis of Heart Rates Using Machine Learning Techniques.

International journal of environmental research and public health
Heart disease, caused by low heart rate, is one of the most significant causes of mortality in the world today. Therefore, it is critical to monitor heart health by identifying the deviation in the heart rate very early, which makes it easier to dete...

Efficient link prediction in the protein-protein interaction network using topological information in a generative adversarial network machine learning model.

BMC bioinformatics
BACKGROUND: The investigation of possible interactions between two proteins in intracellular signaling is an expensive and laborious procedure in the wet-lab, therefore, several in silico approaches have been implemented to narrow down the candidates...

Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling.

Environmental science and pollution research international
Dam safety assessment is important to implement the appropriate measures to avoid a dam break disaster as part of the water reservoirs management process. Prediction-based approaches are valuable to compare the actual measurements with the simulated ...