Marwa Obayya¹, Nadhem NEMRI², Lubna A. Alharbi³, Mohamed K. Nour⁴, Mrim M. Alnfiai⁵, Mohammed Abdullah Al-Hagery⁶, Nermin M. Salem⁷, Mesfer Al Duhayyim^8,*

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3151-3166, 2023, DOI:10.32604/cmc.2023.032765

Abstract With new developments experienced in Internet of Things (IoT), wearable, and sensing technology, the value of healthcare services has enhanced. This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare. Bio-medical Electrocardiogram (ECG) signals are generally utilized in examination and diagnosis of Cardiovascular Diseases (CVDs) since it is quick and non-invasive in nature. Due to increasing number of patients in recent years, the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients. In such scenario computer-assisted automated diagnostic tools are important for classification of ECG signals. The current study… More >

Mahmoud Ragab^1,2,3,*, Maged Mostafa Mahmoud^4,5,6, Amer H. Asseri^2,7, Hani Choudhry^2,7, Haitham A. Yacoub⁸

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3279-3295, 2023, DOI:10.32604/cmc.2023.031037

Abstract Colorectal carcinoma (CRC) is one such dispersed cancer globally and also prominent one in causing cancer-based death. Conventionally, pathologists execute CRC diagnosis through visible scrutinizing under the microscope the resected tissue samples, stained and fixed through Haematoxylin and Eosin (H&E). The advancement of graphical processing systems has resulted in high potentiality for deep learning (DL) techniques in interpretating visual anatomy from high resolution medical images. This study develops a slime mould algorithm with deep transfer learning enabled colorectal cancer detection and classification (SMADTL-CCDC) algorithm. The presented SMADTL-CCDC technique intends to appropriately recognize the occurrence of colorectal cancer. To accomplish this,… More >

P. Pandi Chandran^1,*, N. Hema Rajini², M. Jeyakarthic³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3349-3364, 2023, DOI:10.32604/iasc.2023.029946

Abstract Cybercrime has increased considerably in recent times by creating new methods of stealing, changing, and destroying data in daily lives. Portable Document Format (PDF) has been traditionally utilized as a popular way of spreading malware. The recent advances of machine learning (ML) and deep learning (DL) models are utilized to detect and classify malware. With this motivation, this study focuses on the design of mayfly optimization with a deep belief network for PDF malware detection and classification (MFODBN-MDC) technique. The major intention of the MFODBN-MDC technique is for identifying and classifying the presence of malware exist in the PDFs. The… More >

Monika Khandelwal¹, Ranjeet Kumar Rout¹, Saiyed Umer², Kshira Sagar Sahoo³, NZ Jhanjhi^4,*, Mohammad Shorfuzzaman⁵, Mehedi Masud⁵

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3587-3598, 2023, DOI:10.32604/iasc.2023.029785

Abstract Classification of the patterns is a crucial structure of research and applications. Using fuzzy set theory, classifying the patterns has become of great interest because of its ability to understand the parameters. One of the problems observed in the fuzzification of an unknown pattern is that importance is given only to the known patterns but not to their features. In contrast, features of the patterns play an essential role when their respective patterns overlap. In this paper, an optimal fuzzy nearest neighbor model has been introduced in which a fuzzification process has been carried out for the unknown pattern using… More >

Mesfer Al Duhayyim^1,*, Areej A. Malibari², Sami Dhahbi³, Mohamed K. Nour⁴, Isra Al-Turaiki⁵, Marwa Obayya⁶, Abdullah Mohamed⁷

Computer Systems Science and Engineering, Vol.45, No.1, pp. 753-767, 2023, DOI:10.32604/csse.2023.030556

Abstract Recently, computer aided diagnosis (CAD) model becomes an effective tool for decision making in healthcare sector. The advances in computer vision and artificial intelligence (AI) techniques have resulted in the effective design of CAD models, which enables to detection of the existence of diseases using various imaging modalities. Oral cancer (OC) has commonly occurred in head and neck globally. Earlier identification of OC enables to improve survival rate and reduce mortality rate. Therefore, the design of CAD model for OC detection and classification becomes essential. Therefore, this study introduces a novel Computer Aided Diagnosis for OC using Sailfish Optimization with… More >

N. Karthikeyan², P. Sivaprakash^1,*, S. Karthik²

Computer Systems Science and Engineering, Vol.45, No.1, pp. 671-685, 2023, DOI:10.32604/csse.2023.029984

Abstract Intrusion detection systems (IDS) are one of the most promising ways for securing data and networks; In recent decades, IDS has used a variety of categorization algorithms. These classifiers, on the other hand, do not work effectively unless they are combined with additional algorithms that can alter the classifier’s parameters or select the optimal sub-set of features for the problem. Optimizers are used in tandem with classifiers to increase the stability and with efficiency of the classifiers in detecting invasion. These algorithms, on the other hand, have a number of limitations, particularly when used to detect new types of threats.… More >

Mesfer Al Duhayyim^1,*, Areej A. Malibari², Marwa Obayya³, Mohamed K. Nour⁴, Ahmed S. Salama⁵, Mohamed I. Eldesouki⁶, Abu Sarwar Zamani⁷, Mohammed Rizwanullah⁷

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5473-5489, 2022, DOI:10.32604/cmc.2022.031976

Abstract The skeletal bone age assessment (BAA) was extremely implemented in development prediction and auxiliary analysis of medicinal issues. X-ray images of hands were detected from the estimation of bone age, whereas the ossification centers of epiphysis and carpal bones are important regions. The typical skeletal BAA approaches remove these regions for predicting the bone age, however, few of them attain suitable efficacy or accuracy. Automatic BAA techniques with deep learning (DL) methods are reached the leading efficiency on manual and typical approaches. Therefore, this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with… More >

Hadil Shaiba¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Radwa Marzouk⁴, Heba Mohsen⁵, Manar Ahmed Hamza^6,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6425-6441, 2022, DOI:10.32604/cmc.2022.031625

Abstract Phishing is one of the simplest ways in cybercrime to hack the reliable data of users such as passwords, account identifiers, bank details, etc. In general, these kinds of cyberattacks are made at users through phone calls, emails, or instant messages. The anti-phishing techniques, currently under use, are mainly based on source code features that need to scrape the webpage content. In third party services, these techniques check the classification procedure of phishing Uniform Resource Locators (URLs). Even though Machine Learning (ML) techniques have been lately utilized in the identification of phishing, they still need to undergo feature engineering since… More >

Thien Khai Tran¹, Kha Tu Huynh^2,*, Dac-Nhuong Le³, Muhammad Arif⁴, Hoa Minh Dinh¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2479-2491, 2023, DOI:10.32604/iasc.2023.029078

Abstract Environmental pollution has had substantial impacts on human life, and trash is one of the main sources of such pollution in most countries. Trash classification from a collection of trash images can limit the overloading of garbage disposal systems and efficiently promote recycling activities; thus, development of such a classification system is topical and urgent. This paper proposed an effective trash classification system that relies on a classification module embedded in a hard-ware setup to classify trash in real time. An image dataset is first augmented to enhance the images before classifying them as either inorganic or organic trash. The… More >

Areej A. Malibari¹, Marwa Obayya², Mohamed K. Nour³, Amal S. Mehanna⁴, Manar Ahmed Hamza^5,*, Abu Sarwar Zamani⁵, Ishfaq Yaseen⁵, Abdelwahed Motwakel⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4123-4138, 2022, DOI:10.32604/cmc.2022.030492

Abstract With the rapid increase of new cases with an increased mortality rate, cancer is considered the second and most deadly disease globally. Breast cancer is the most widely affected cancer worldwide, with an increased death rate percentage. Due to radiologists’ processing of mammogram images, many computer-aided diagnoses have been developed to detect breast cancer. Early detection of breast cancer will reduce the death rate worldwide. The early diagnosis of breast cancer using the developed computer-aided diagnosis (CAD) systems still needed to be enhanced by incorporating innovative deep learning technologies to improve the accuracy and sensitivity of the detection system with… More >