Brain tumor segmentation of MRI images: A comprehensive review on the application of artificial intelligence tools

R Ranjbarzadeh, A Caputo, EB Tirkolaee… - Computers in biology …, 2023 - Elsevier
Background Brain cancer is a destructive and life-threatening disease that imposes
immense negative effects on patients' lives. Therefore, the detection of brain tumors at an …

On hyperparameter optimization of machine learning algorithms: Theory and practice

L Yang, A Shami - Neurocomputing, 2020 - Elsevier
Abstract Machine learning algorithms have been used widely in various applications and
areas. To fit a machine learning model into different problems, its hyper-parameters must be …

[HTML][HTML] Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management

V Pasupuleti, B Thuraka, CS Kodete, S Malisetty - Logistics, 2024 - mdpi.com
Background: In the current global market, supply chains are increasingly complex,
necessitating agile and sustainable management strategies. Traditional analytical methods …

dbscan: Fast density-based clustering with R

M Hahsler, M Piekenbrock, D Doran - Journal of Statistical Software, 2019 - jstatsoft.org
This article describes the implementation and use of the R package dbscan, which provides
complete and fast implementations of the popular density-based clustering algorithm …

IoT data analytics in dynamic environments: From an automated machine learning perspective

L Yang, A Shami - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
With the wide spread of sensors and smart devices in recent years, the data generation
speed of the Internet of Things (IoT) systems has increased dramatically. In IoT systems …

A novel ranking-based clustering approach for hyperspectral band selection

S Jia, G Tang, J Zhu, Q Li - IEEE Transactions on Geoscience …, 2015 - ieeexplore.ieee.org
Through imaging the same spatial area by hyperspectral sensors at different spectral
wavelengths simultaneously, the acquired hyperspectral imagery often contains hundreds of …

[HTML][HTML] Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)

MK Hasan, MA Alam, S Roy, A Dutta, MT Jawad… - Informatics in Medicine …, 2021 - Elsevier
Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
intending the primary solution scheme for the datasets containing one or more missing …

Multi-feature, multi-modal, and multi-source social event detection: A comprehensive survey

I Afyouni, Z Al Aghbari, RA Razack - Information Fusion, 2022 - Elsevier
The tremendous growth of event dissemination over social networks makes it very
challenging to accurately discover and track exciting events, as well as their evolution and …

Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data

S Park, Y Xu, L Jiang, Z Chen, S Huang - Annals of Tourism Research, 2020 - Elsevier
The advancement of mobile technology provides an opportunity to obtain the real-time
information of travelers, such as their spatial and temporal behaviors, during their visits to a …

[HTML][HTML] Reviewing the application of machine learning methods to model urban form indicators in planning decision support systems: Potential, issues and …

SCK Tekouabou, EB Diop, R Azmi, R Jaligot… - Journal of King Saud …, 2022 - Elsevier
Modern cities dynamically face several challenges including digitalization, sustainability,
resilience and economic development. Urban planners and designers must develop urban …