Guest Editors
Dr. Muhammad Irfan, Najran University, Saudi Arabia.
Dr. Adam Glowacz, AGH University of Science and Technology, Poland.
Prof. Dr. Thompson Sarkodie-Gyan, University of Texas at El Paso, USA.
Summary
The aim of this special issue is to publish
the latest research on modern and sustainable health infrastructure, modern
technologies for smart diagnostics, e-health and reliable decisions. The
increasing world population is causing an increase in natural resources usage,
the forests are being replaced with the buildings, food consumption has been
increased resulting in an increase of waste, more traffic on the roads causing
a more polluted environment. Consequently, human health is at great risk and
faces global challenges of epidemics and pandemics. Thus, the greatest challenge
for researchers in the near future will be to design and innovate smart systems
that can meet the increasing demand for healthcare and build a sustainable
healthcare system. The special issue is intended for researchers, local
governments, graduate students and practicing engineers with an interest in the
technologies related to sustainable healthcare for smart cities. It will cover
the applications of Artificial Intelligence, the Internet of Things (IoT),
Biomaterials and Nanotechnologies to solve several issues of the community such
as modern healthcare systems.
The modern healthcare systems need to be
simpler and easier to access.
Therefore, this special issue will focus on
but not limited to the following topics:
Potential topics include but are not
limited to the following:
• AI for future health management systems
• Image processing for biomedical engineering
• Signal processing for biomedical engineering
• Condition monitoring of medical instruments
• Medical data security
• IoT and AI for early diagnosis of cancer
• IoT and AI for early diagnosis of brain tumors
• Impact of environmental changes on human health
Keywords
Cancer diagnosis; Intelligent healthcare systems; Artificial intelligence; Machine learning; Deep Learning; Internet of things; Big data; Smart cities; Smart healthcare; Smart resource management; Cybersecurity attacks on medical data
Published Papers
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Open Access
ARTICLE
A Novel Convolutional Neural Networks-Fused Shallow Classifier for Breast Cancer Detection
Sharifa Khalid Alduraibi
Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1321-1334, 2022, DOI:10.32604/iasc.2022.025021
（This article belongs to this Special Issue:
Intelligent Systems for Smart and Sustainable Healthcare)
Abstract This paper proposes a fused methodology based upon convolutional neural networks and a shallow classifier to diagnose and differentiate breast cancer between malignant lesions and benign lesions. First, various pre-trained convolutional neural networks are used to calculate the features of breast ultrasonography (BU) images. Then, the computed features are used to train the different shallow classifiers like the tree, naïve Bayes, support vector machine (SVM), k-nearest neighbors, ensemble, and neural network. After extensive training and testing, the DenseNet-201, MobileNet-v2, and ResNet-101 trained SVM show high accuracy. Furthermore, the best BU features are merged to increase the classification accuracy at the…
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