Ahmad F Subahi^*, Areej Athama

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 3801-3816, 2023, DOI:10.32604/cmc.2023.034522

Abstract With the rapid growth in the availability of digital health-related data, there is a great demand for the utilization of intelligent information systems within the healthcare sector. These systems can manage and manipulate this massive amount of health-related data and encourage different decision-making tasks. They can also provide various sustainable health services such as medical error reduction, diagnosis acceleration, and clinical services quality improvement. The intensive care unit (ICU) is one of the most important hospital units. However, there are limited rooms and resources in most hospitals. During times of seasonal diseases and pandemics, ICUs face high admission demand. In… More >

Shahbaz Sikandar¹, Rabbia Mahum¹, Suliman Aladhadh^2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2007-2025, 2023, DOI:10.32604/csse.2023.037723

Abstract Agriculture plays an important role in the economy of any country. Approximately half of the population of developing countries is directly or indirectly connected to the agriculture field. Many farmers do not choose the right crop for cultivation depending on their soil type, crop type, and climatic requirements like rainfall. This wrong decision of crop selection directly affects the production of the crops which leads to yield and economic loss in the country. Many parameters should be observed such as soil characteristics, type of crop, and environmental factors for the cultivation of the right crop. Manual decision-making is time-taking and… More >

Tamim Alkhalifah^1,*, Jimmy Singla², Fahad Alurise¹

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3559-3582, 2023, DOI:10.32604/csse.2023.036534

Abstract The diagnosis of liver fibrosis (LF) is crucial as it is a deadly and life-threatening disease. Artificial intelligence techniques aid doctors by using the previous data on health and making a diagnostic system, which helps to take decisions about patients’ health as experts can. The historical data of a patient’s health can have vagueness, inaccurate, and can also have missing values. The fuzzy logic theory can deal with these issues in the dataset. In this paper, a multilayer fuzzy expert system is developed to diagnose LF. The model is created by using multiple layers of the fuzzy logic approach. This… More >

Wencong Liu¹, Ahmed Mostafa Khalil^2,*, Rehab Basheer³, Yong Lin⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2715-2730, 2023, DOI:10.32604/cmes.2023.024755

Abstract In early December 2019, a new virus named “2019 novel coronavirus (2019-nCoV)” appeared in Wuhan, China. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. In the current work, we will propose a novel fuzzy soft modal (i.e., fuzzy-soft expert system) for early detection of COVID-19. The main construction of the fuzzy-soft expert system consists of five portions. The exploratory study includes sixty patients (i.e., forty males and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert system depended on five symptoms of COVID-19 (i.e., shortness of breath, sore… More > Graphic Abstract

Praveen Talari^1,*, A. Suresh², M. G. Kavitha³

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1053-1067, 2023, DOI:10.32604/iasc.2023.027024

Abstract As per World Health Organization report which was released in the year of 2019, Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world. Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it. Among the diabetics, it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2. To avoid this situation, we… More >

Kathiravan Srinivasan¹, Lalit Garg^2,*, Bor-Yann Chen³, Abdulellah A. Alaboudi⁴, N. Z. Jhanjhi⁵, Chang-Tang Chang⁶, B. Prabadevi¹, N. Deepa¹

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 17-30, 2021, DOI:10.32604/iasc.2021.018380

Abstract Expert Systems are interactive and reliable computer-based decision-making systems that use both facts and heuristics for solving complex decision-making problems. Generally, the cyclic voltammetry (CV) experiments are executed a random number of times (cycles) to get a stable production of power. However, presently there are not many algorithms or models for predicting the power generation stable criteria in microbial fuel cells. For stability analysis of Medicinal herbs’ CV profiles, an expert system driven by the augmented K-means clustering algorithm is proposed. Our approach requires a dataset that contains voltage-current relationships from CV experiments on the related subjects (plants/herbs). This new… More >

M. Jayalakshmi¹, Lalit Garg^2,*, K. Maharajan³, K. Jayakumar⁴, Kathiravan Srinivasan⁵, Ali Kashif Bashir⁶, K. Ramesh⁷

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2431-2447, 2021, DOI:10.32604/cmc.2021.015352

Abstract In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID’19 patients and quarantined people. It identifies the patient’s medical and psychological condition based… More >

Kazim Sari

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 405-412, 2018, DOI:10.1080/10798587.2017.1352258

Abstract Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review… More >

Shengqun Fang¹, Zhiping Cai^1,*, Wencheng Sun¹, Anfeng Liu², Fang Liu³, Zhiyao Liang⁴, Guoyan Wang⁵

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI: 10.3970/cmc.2018.02289

Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease categories, and compare this method… More >