S. Amutha^*, J. Raja Sekar

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1863-1880, 2023, DOI:10.32604/iasc.2023.028903 - 05 January 2023

Abstract In this digital era, Cardio Vascular Disease (CVD) has become the leading cause of death which has led to the mortality of 17.9 million lives each year. Earlier Diagnosis of the people who are at higher risk of CVDs helps them to receive proper treatment and helps prevent deaths. It becomes inevitable to propose a solution to predict the CVD with high accuracy. A system for predicting Cardio Vascular Disease using Deep Neural Network with Binarized Butterfly Optimization Algorithm (DNN–BBoA) is proposed. The BBoA is incorporated to select the best features. The optimal features are… More >

Ghada Abdulsalam¹, Souham Meshoul^2,*, Hadil Shaiba³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 761-779, 2023, DOI:10.32604/iasc.2023.032262 - 29 September 2022

Abstract Nowadays, quantum machine learning is attracting great interest in a wide range of fields due to its potential superior performance and capabilities. The massive increase in computational capacity and speed of quantum computers can lead to a quantum leap in the healthcare field. Heart disease seriously threatens human health since it is the leading cause of death worldwide. Quantum machine learning methods can propose effective solutions to predict heart disease and aid in early diagnosis. In this study, an ensemble machine learning model based on quantum machine learning classifiers is proposed to predict the risk… More >

C. Santhosh Kumar¹, K. Vishnu Kumar^2,*

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2893-2907, 2023, DOI:10.32604/iasc.2023.029669 - 17 August 2022

Abstract Privacy-preserving online disease prediction and diagnosis are critical issues in the emerging edge-cloud-based healthcare system. Online patient data processing from remote places may lead to severe privacy problems. Moreover, the existing cloud-based healthcare system takes more latency and energy consumption during diagnosis due to offloading of live patient data to remote cloud servers. Solve the privacy problem. The proposed research introduces the edge-cloud enabled privacy-preserving healthcare system by exploiting additive homomorphic encryption schemes. It can help maintain the privacy preservation and confidentiality of patients’ medical data during diagnosis of Parkinson’s disease. In addition, the energy More >

S. Raghavendra¹, Vasudev Parvati², R. Manjula³, Ashok Kumar Nanda⁴, Ruby Singh⁵, D. Lakshmi⁶, S. Velmurugan^7,*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1353-1368, 2023, DOI:10.32604/iasc.2023.027977 - 19 July 2022

Abstract In contemporary medicine, cardiovascular disease is a major public health concern. Cardiovascular diseases are one of the leading causes of death worldwide. They are classified as vascular, ischemic, or hypertensive. Clinical information contained in patients’ Electronic Health Records (EHR) enables clinicians to identify and monitor heart illness. Heart failure rates have risen dramatically in recent years as a result of changes in modern lifestyles. Heart diseases are becoming more prevalent in today’s medical setting. Each year, a substantial number of people die as a result of cardiac pain. The primary cause of these deaths is… More >

M. Vinoth Kumar^1,*, M. Prakash², M. Naresh Kumar³, H. Abdul Shabeer⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1277-1293, 2023, DOI:10.32604/iasc.2023.025591 - 19 July 2022

Abstract The most noteworthy neurodegenerative disorder nationwide is apparently the Alzheimer's disease (AD) which ha no proven viable treatment till date and despite the clinical trials showing the potential of preclinical therapy, a sensitive method for evaluating the AD has to be developed yet. Due to the correlations between ocular and brain tissue, the eye (retinal blood vessels) has been investigated for predicting the AD. Hence, en enhanced method named Enhanced Long Short Term Memory (E-LSTM) has been proposed in this work which aims at finding the severity of AD from ocular biomarkers. To find the… More >

Ahmed ElShafee¹, Walid El-Shafai², Abdulaziz Alarifi^3,*, Mohammed Amoon³, Aman Singh⁴, Moustafa H. Aly⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4157-4177, 2022, DOI:10.32604/cmc.2022.028847 - 16 June 2022

Abstract Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine. Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable, consistent, and timely, successfully lowering mortality rates, particularly during endemics and pandemics. To prevent this pandemic’s rapid and widespread, it is vital to quickly identify, confine, and treat affected individuals. The need for auxiliary computer-aided diagnostic (CAD) systems has grown. Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus. Utilizing advanced convolutional neural network (CNN)… More >

R. Gopi^1,*, S. Veena², S. Balasubramanian³, D. Ramya⁴, P. Ilanchezhian⁵, A. Harshavardhan⁶, Zatin Gupta⁷

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1215-1230, 2022, DOI:10.32604/iasc.2022.025792 - 03 May 2022

Abstract In this modern era, the transformation of conventional objects into smart ones via internet vitality, data management, together with many more are the main aim of the Internet of Things (IoT) centered Big Data (BD) analysis. In the past few years, significant augmentation in the IoT-centered Healthcare (HC) monitoring can be seen. Nevertheless, the merging of health-specific parameters along with IoT-centric Health Monitoring (HM) systems with BD handling ability is turned out to be a complicated research scope. With the aid of Map-Reduce and LSQN³ techniques, this paper proposed IoT devices in Wireless Sensors Networks (WSN)… More >

Sridharan Kannan^*

CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.2, pp. 677-694, 2022, DOI:10.32604/cmes.2022.018580 - 14 March 2022

Abstract With the worldwide analysis, heart disease is considered a significant threat and extensively increases the mortality rate. Thus, the investigators mitigate to predict the occurrence of heart disease in an earlier stage using the design of a better Clinical Decision Support System (CDSS). Generally, CDSS is used to predict the individuals’ heart disease and periodically update the condition of the patients. This research proposes a novel heart disease prediction system with CDSS composed of a clustering model for noise removal to predict and eliminate outliers. Here, the Synthetic Over-sampling prediction model is integrated with the… More >

Faisal Saeed^1,2,*, Mohammad Al-Sarem^1,3, Muhannad Al-Mohaimeed¹, Abdelhamid Emara^1,4, Wadii Boulila^1,5, Mohammed Alasli¹, Fahad Ghabban¹

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5639-5658, 2022, DOI:10.32604/cmc.2022.023124 - 14 January 2022

Abstract Several millions of people suffer from Parkinson's disease globally. Parkinson's affects about 1% of people over 60 and its symptoms increase with age. The voice may be affected and patients experience abnormalities in speech that might not be noticed by listeners, but which could be analyzed using recorded speech signals. With the huge advancements of technology, the medical data has increased dramatically, and therefore, there is a need to apply data mining and machine learning methods to extract new knowledge from this data. Several classification methods were used to analyze medical data sets and diagnostic… More >

Hicham Moujahid¹, Bouchaib Cherradi^1,2,*, Mohammed Al-Sarem³, Lhoussain Bahatti¹, Abou Bakr Assedik Mohammed Yahya Eljialy⁴, Abdullah Alsaeedi³, Faisal Saeed³

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 723-745, 2022, DOI:10.32604/iasc.2022.022179 - 17 November 2021

Abstract With daily increasing of suspected COVID-19 cases, the likelihood of the virus mutation increases also causing the appearance of virulent variants having a high level of replication. Automatic diagnosis methods of COVID-19 disease are very important in the medical community. An automatic diagnosis could be performed using machine and deep learning techniques to analyze and classify different lung X-ray images. Many research studies proposed automatic methods for detecting and predicting COVID-19 patients based on their clinical data. In the leak of valid X-ray images for patients with COVID-19 datasets, several researchers proposed to use augmentation… More >