A systematic review of time series classification techniques used in biomedical applications
Background: Digital clinical measures collected via various digital sensing technologies
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …
such as smartphones, smartwatches, wearables, and ingestible and implantable sensors …
PToPI: A comprehensive review, analysis, and knowledge representation of binary classification performance measures/metrics
Although few performance evaluation instruments have been used conventionally in
different machine learning-based classification problem domains, there are numerous ones …
different machine learning-based classification problem domains, there are numerous ones …
Develo** a national data-driven construction safety management framework with interpretable fatal accident prediction
Occupational accidents are frequent in the construction industry, containing significant risks
in the working environment. Therefore, early designation, taking preventive actions, and …
in the working environment. Therefore, early designation, taking preventive actions, and …
Machine learning-based prediction of air quality index and air quality grade: a comparative analysis
The purpose of this study was to compare different machine learning models for predicting
daily air quality index (AQI) and evaluating air quality grade (AQG). The study used publicly …
daily air quality index (AQI) and evaluating air quality grade (AQG). The study used publicly …
Tumor diagnosis against other brain diseases using T2 MRI brain images and CNN binary classifier and DWT
Purpose: Brain tumors are diagnosed and classified manually and noninvasively by
radiologists using Magnetic Resonance Imaging (MRI) data. The risk of misdiagnosis may …
radiologists using Magnetic Resonance Imaging (MRI) data. The risk of misdiagnosis may …
Predictive video analytics in online courses: A systematic literature review
The purpose of this study was to investigate the use of predictive video analytics in online
courses in the literature. A systematic literature review was performed based on a hybrid …
courses in the literature. A systematic literature review was performed based on a hybrid …
Gaining insights in datasets in the shade of “garbage in, garbage out” rationale: Feature space distribution fitting
G Canbek - Wiley Interdisciplinary Reviews: Data Mining and …, 2022 - Wiley Online Library
This article emphasizes comprehending the “Garbage In, Garbage Out”(GIGO) rationale and
ensuring the dataset quality in Machine Learning (ML) applications to achieve high and …
ensuring the dataset quality in Machine Learning (ML) applications to achieve high and …
[HTML][HTML] Automatic detection of scratching events on vehicles with audio-based spectrograms
The identification of damages, specifically scratches, on the structure of vehicles is a
challenge to many businesses. In most automobile industries, this process is mainly …
challenge to many businesses. In most automobile industries, this process is mainly …
PPDF-FedTMI: A Federated Learning-based Transport Mode Inference Model with Privacy-Preserving Data Fusion
Abstract Mobile Crowd-Sensing (MCS) represents a distributed data fusion system that
aggregates diverse sources to enhance inference capabilities beyond any single input. As …
aggregates diverse sources to enhance inference capabilities beyond any single input. As …
Preference-driven classification measure
Classification is one of the main problems of machine learning, and assessing the quality of
classification is one of the most topical tasks, all the more difficult as it depends on many …
classification is one of the most topical tasks, all the more difficult as it depends on many …