C. S. S. Anupama¹, L. Natrayan², E. Laxmi Lydia³, Abdul Rahaman Wahab Sait⁴, José Escorcia-Gutierrez⁵, Margarita Gamarra^6,*, Romany F. Mansour⁷

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1297-1313, 2022, DOI:10.32604/cmc.2022.018396 - 07 September 2021

Abstract Nowadays, quality improvement and increased accessibility to patient data, at a reasonable cost, are highly challenging tasks in healthcare sector. Internet of Things (IoT) and Cloud Computing (CC) architectures are utilized in the development of smart healthcare systems. These entities can support real-time applications by exploiting massive volumes of data, produced by wearable sensor devices. The advent of evolutionary computation algorithms and Deep Learning (DL) models has gained significant attention in healthcare diagnosis, especially in decision making process. Skin cancer is the deadliest disease which affects people across the globe. Automatic skin lesion classification model… More >

Naglaa F. Soliman^1,2, Naglaa S. Ali², Mahmoud I. Aly^2,3, Abeer D. Algarni^1,*, Walid El-Shafai⁴, Fathi E. Abd El-Samie^1,4

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1315-1334, 2022, DOI:10.32604/cmc.2022.017001 - 07 September 2021

Abstract Breast cancer is the most common type of cancer, and it is the reason for cancer death toll in women in recent years. Early diagnosis is essential to handle breast cancer patients for treatment at the right time. Screening with mammography is the preferred examination for breast cancer, as it is available worldwide and inexpensive. Computer-Aided Detection (CAD) systems are used to analyze medical images to detect breast cancer, early. The death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after operations. Processing of mammogram images has four main… More >

G. Reshma^1,*, Chiai Al-Atroshi², Vinay Kumar Nassa³, B.T. Geetha⁴, Gurram Sunitha⁵, Mohammad Gouse Galety⁶, S. Neelakandan⁷

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 621-634, 2022, DOI:10.32604/iasc.2022.019117 - 03 September 2021

Abstract In recent years, intelligent automation in the healthcare sector becomes more familiar due to the integration of artificial intelligence (AI) techniques. Intelligent healthcare systems assist in making better decisions, which further enable the patient to provide improved medical services. At the same time, skin lesion is a deadly disease that affects people of all age groups. Skin lesion segmentation and classification play a vital part in the earlier and precise skin cancer diagnosis by intelligent systems. However, the automated diagnosis of skin lesions in dermoscopic images is challenging because of the problems such as artifacts… More >

A. Thasil Mohamed, Sundar Santhoshkumar^*

Computer Systems Science and Engineering, Vol.40, No.1, pp. 191-205, 2022, DOI:10.32604/csse.2022.016754 - 26 August 2021

Abstract Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases… More >

Qingzhu Song¹, Fenglan Zhang², Tian Yuan², Yulong Wei²

European Cytokine Network, Vol.32, No.2, pp. 39-47, 2021, DOI:10.1684/ecn.2021.0468

Abstract Breast cancer is by far the most common malignancy found in women and causes a significant public health problem around the world. Early diagnosis of cancer plays an important role in successful treatment and survival of patients. This study aims to investigate the possibility of plasma Tie2 to be used as a biomarker for diagnosis of breast cancer. In total, 20 healthy volunteers and 33 breast cancer patients were considered for this study. The level of Tie2 in plasma was detected using the ELISA technique and immunohistochemistry was performed to measure the expression of Tie2… More >

Saqlain Abbas^1,2,*, Zulkarnain Abbas³, Xiaotong Tu⁴, Yanping Zhu¹

Journal on Artificial Intelligence, Vol.3, No.3, pp. 97-113, 2021, DOI:10.32604/jai.2021.023020 - 25 January 2022

Abstract The performance and reliability of structural components are greatly influenced by the presence of any abnormality in them. To this purpose, structural health monitoring (SHM) is recognized as a necessary tool to ensure the safety precautions and efficiency of both mechanical and civil infrastructures. Till now, most of the previous work has emphasized the functioning of several SHM techniques and systematic changes in SHM execution. However, there exist insufficient data in the literature regarding the patent-based technological developments in the SHM research domain which might be a useful source of detailed information for worldwide research… More >

Asmaa E. E. Ali^*, Mofreh Mohamed Salem, Mahmoud Badway, Ali I. EL Desouky

Journal on Artificial Intelligence, Vol.3, No.3, pp. 81-96, 2021, DOI:10.32604/jai.2021.022433 - 25 January 2022

Abstract Breast cancer (BrC) is now the world’s leading cause of death for women. Early detection and effective treatment of this disease are the only rescues to reduce BrC mortality. The prediction of BrC diseases is very difficult because it is not an individual disease but a mixture of various diseases. Many researchers have used different techniques such as classification, Machine Learning (ML), and Deep Learning (DL) of the prediction of the breast tumor into Benign and Malignant. However, still there is a scope to introduce appropriate techniques for developing and implementing a more effective diagnosis… More >

Sunil Kr. Jha^1,*, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 567-594, 2021, DOI:10.32604/cmes.2021.016817 - 08 October 2021

Abstract Health care data mining is noteworthy in disease diagnosis and recognition procedures. There exist several potentials to further improve the performance of machine learning based-classification methods in healthcare data analysis. The selection of a substantial subset of features is one of the feasible approaches to achieve improved recognition results of classification methods in disease diagnosis prediction. In the present study, a novel combined approach of feature generation using latent semantic analysis (LSA) and selection using ranker search (RAS) has been proposed to improve the performance of classification methods in lymph disease diagnosis prediction. The performance… More >

Junyu Chen¹, Yunwen Feng^1,*, Cheng Lu^1,2, Chengwei Fei²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1013-1027, 2021, DOI:10.32604/cmes.2021.016980 - 08 October 2021

Abstract As the key component in aeroengine rotor systems, the health status of rolling bearings directly influences the reliability and safety of aeroengine rotor systems. In order to monitor rolling bearing conditions, a fusion fault diagnosis method, namely empirical mode decomposition (EMD)-Mahalanobis distance (E2MD) and improved wavelet threshold (IWT) (E2MD-IWT) for vibrational signals and acoustic emission (AE) signals is developed to improve the diagnostic accuracy of rolling bearings. The IWT method is proposed with a hard wavelet threshold and a soft wavelet threshold. Moreover, it is shown to be effective through numerical simulation. EMD is utilized… More >

Junding Sun^1,3,#, Xiang Li^1,#, Chaosheng Tang^1,*, Shixin Chen^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 729-753, 2021, DOI:10.32604/cmes.2021.016416 - 08 October 2021

Abstract Purpose: As to January 11, 2021, coronavirus disease (COVID-19) has caused more than 2 million deaths worldwide. Mainly diagnostic methods of COVID-19 are: (i) nucleic acid testing. This method requires high requirements on the sample testing environment. When collecting samples, staff are in a susceptible environment, which increases the risk of infection. (ii) chest computed tomography. The cost of it is high and some radiation in the scan process. (iii) chest X-ray images. It has the advantages of fast imaging, higher spatial recognition than chest computed tomography. Therefore, our team chose the chest X-ray images as More >