Calls for Papers (special): International Journal of Information Technologies and Systems Approach (IJITSA)


Special Issue On: Advances in Intelligent Information Systems for health informatics

Submission Due Date
5/31/2021

Guest Editors
Dr. Faisal Saeed, Taibah University, Saudi Arabia
Dr. Fathey Mohammed, Universiti Utara Malaysia, Malaysia
Dr. Nadhmi Gazem, Taibah University, Saudi Arabia

Introduction
The quality of health care systems can be improved by the innovative and intelligent methods of health informatics, which can effectively collect, manipulate, store and retrieve the healthcare digital information (Shekelle, Morton and Keeler, 2006). Its applications in healthcare are used for evidence-based practice, informed decision-making and efficient resource management (Hashim, Rahim and Alam, 2007). In many countries that are facing issues in lack of policies, privacy, confidentiality and others, the health informatics has a great role in improving the quality of healthcare-related services (Kothari et al., 2008). As the intelligent information systems have been widely used, it becomes possible to provide health care services to remote places by health care professionals (Anwar et al., 2013).

The artificial intelligence has been widely applied in the medical and health informatics studies (Dilsizian and Siegel, 2014; Patel et al., 2009; Jha and Topol, 2016). It uses complex methods and algorithms to work on healthcare data, extract its features and discover hidden patterns to make better decisions in clinical practice. It can utilize the given feedback to improve the future decisions. The intelligent systems can provide medical doctors with the recent and useful information from online books, journals and other materials (Jiang et al., 2017; Pearson, 2020).

Recently, the developments in intelligent methods have rapidly increased. The scientists are working on several developed methods such as deep learning, internet of things, smart computing, and others. Utilizing these intelligent methods in healthcare applications is very useful. However, there are many challenges still faced to deal with the big healthcare data, obtaining accurate predictions models, developing fully intelligent healthcare systems and so on. Therefore, this special issue will discuss the main topics in the advances on intelligent information systems in healthcare and also other similar fields.

REFERENCES

Anwar, F., R. Kumar, S. Sulaiman, and D. D. P. Dominic. "Health informatics in Pakistan: Current scenario in capacity development for health professionals." the Health 4 (2013): 62-65.

Dilsizian SE, Siegel EL. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment. Curr Cardiol Rep 2014;16:441.

Hashim MJ, Rahim MF, Alam AY. Training in reference management software--a part of new medical informatics workshops in Pakistan. J Ayub Med Coll Abbottabad. 2007;19:70-1.

Jha S, Topol EJ. Adapting to Artificial Intelligence: radiologists and pathologists as information specialists. JAMA 2016;316:2353–4.

Jiang, Fei, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, and Yongjun Wang. "Artificial intelligence in healthcare: past, present and future." Stroke and vascular neurology 2, no. 4 (2017): 230-243.

Kothari A, Driedger SM, Bickford J, Morrison J, Sawada M, et al. Mapping as a knowledge translation tool for Ontario Early Years Centres: views from data analysts and managers. Implement Sci. 2008;3:4.

Shekelle PG, Morton SC, Keeler EB. Costs and benefits of health information technology. Evid Rep Technol Assess (Full Rep). 2006;132:1-71.

Patel VL, Shortliffe EH, Stefanelli M, et al. The coming of age of artificial intelligence in medicine. Artif Intell Med 2009;46:5–17.

Pearson T. How to replicate Watson hardware and systems design for your own use in your basement. 2011 https://www.ibm.com/ developerworks/community/blogs/InsideSystemStorage/entry/ibm_ watson_how_to_build_your_own_watson_jr_in_your_basement7? lang=en (accessed 1 Jun 2020).

Objective
This special issue aims to present and discuss the advances of intelligent information systems in health informatics and related fields. It will also improve our theoretical and technical knowledge on this very important discipline.

Recommended Topics
• Health Information Sciences
• Medical Image Processing & Techniques
• Data Mining in Healthcare
• Big Data in Healthcare
• Machine Learning in Healthcare
• Bioinformatics & Biostatistics
• Applications of Healthcare Information Systems
• Mobile applications for patient care
• Medical Image Processing & Techniques
• Management of Health Care Communication Systems
• Business Intelligence for Health Informatics
• Knowledge Management in Healthcare Organizations
• E-learning & education in healthcare
• Computer Medical Decision Support Systems
• Medical Informatics
• Organizational IT applications in health care
• Natural Language Processing
• Fuzzy Logic
• Knowledge Acquisition and Expert Systems
• Reasoning and Decision Support Systems
• Hybrid Algorithms
• Genetic Algorithms
• Machine Learning
• Deep Learning
• Multi-Objective Optimization
• Computational Intelligence
• Neural Networks
• Evolutionary Algorithms
• Differential Evolution
• Combinatorial Optimization

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Advances in Intelligent Information Systems for health informatics on or before May 31st, 2021. Prospective authors should note that only original and previously unpublished articles will be considered. INTERESTED AUTHORS MUST CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at https://www.igi-global.com/publish/contributor-resources/journal-guidelines-for-submission/?titleid=1098 PRIOR TO SUBMISSION. All article submissions will be forwarded to at least 3 members of the Editorial Review Board of the journal for double-blind, peer review. Final decision regarding acceptance/revision/rejection will be based on the reviews received from the reviewers.

All inquiries should be directed to the attention of:
Dr. Faisal Saeed
Dr. Fathey Mohammed
Dr. Nadhmi Gazem
Guest Editors
International Journal of Information Technologies and Systems Approach (IJITSA)
Email: alsamet.faisal@gmail.com; fathey.m.ye@gmail.com; nadhmigazem@gmail.com

Special Issue On: Recent Advances in Intelligent Expert Systems for Massively Complex Business Environment

Submission Due Date
6/30/2021

Guest Editors
Dr. Marimuthu Karuppiah, Lead Guest Editor, SRM Institute of Science and Technology, India Dr. Shehzad Ashraf Chaudhry, Istanbul Gelisim University, Turkey Dr. Mohammed H. Alsharif, Sejong University, South Korea

Introduction
Recent advances in computational intelligence and technology have boosted the growth of expert systems enabling its active application on numerous business processes. As enterprises find it more comfortable with expert systems, integrating intelligent approaches such as machine learning, artificial intelligence, and big data techniques offer seamlessly efficient solutions with a roadmap for ambient monitoring and management of the complex business environment. In general, an expert system solves complex problems through its knowledge and reasoning abilities rather than conventional procedures. As expected, expert systems are developed worldwide and are extensively deployed across a variety of business applications. At the same time, the organizations today operate in a complex environment where it cannot just stick to a single product or service. In reality, global companies today do not only expand their services across the regions, but it also grows into other markets. These instances are mainly due to the intense global change, where it impacts on political, economic, social, and technological aspects of the business environment. There is no doubt that all these unpredictability and dynamism translate to complexity, creating massive pressure on the business systems.
Hence, sustaining this complex landscape of the business environment and ensuring the long-term success of the companies is often a difficult task. However, dealing with complexity in the business environment is not a new phenomenon; assessing the strength and opportunities of the organization and employees is a great start, and it leads to surprising effects. AI-assisted intelligent expert systems are highly reliable in this case as they are reasoning based, understandable, responsive, and offer high performance to deal with uncertain business use cases. They exhibit intelligent behavior and expertise in the composite business atmosphere offering qualitative strategies and decisions to deal with unpredictable situations.

Objective
The special section entitled “Recent Advances in Expert Systems for Complex Business Environment” aims to collect the latest approaches and findings on intelligence expert systems and its current challenges across the business application. The key focus will be on using intelligent expert system solutions for forecasting and monitoring of the complex business environment. We presume that the special issue increases the visibility and importance of this research area and contribute to exploring the state-of-the-art analysis of complex business environments with feasible real-time solutions.

Recommended Topics
• New trends in cognitive expert systems for complex business intelligence and management processes
• Strategic decision making and knowledge visualization for complex business environments using intelligent expert systems
• Innovative ways of knowledge management in agile organizations
• Effective ways of inter-organization arrangements using intelligent expert systems
• Recent advances in AI-assisted expert systems for production and new product development across organizations
• Advances in intelligent expert systems for risk analysis in a complex business environment with appropriate solutions
• Data-driven intelligent expert systems to deal with dynamic business management processes
• Advances in knowledge base and intelligent expert to deal with business and industrial marketing in the post-Covid19 era
• Contemporary managerial issues in complex business systems and suitable intelligent expert system based solutions
• Effective ways of sustainable business developments with intelligent expert systems

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Recent Advances in Intelligent Expert Systems for Massively Complex Business Environment on or before June 30, 2021. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

All inquiries should be directed to the attention of:
Dr. Marimuthu Karuppiah
Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology
Delhi NCR Campus, India
Kmarimu@srmist.edu.in, kmarimuthu@ieee.org
Google Scholar:https://scholar.google.co.in/citations?user=AMC7s4AAAAAJ&hl=en
Research Gate: https://www.researchgate.net/profile/Marimuthu_Karuppiah

Special Issue On: Age of Information in Business Intelligence

Submission Due Date
11/11/2021

Guest Editors
Dr. Gunasekaran Manogaran, University of California, Davis, USA
Dr. Hassan Qudrat-Ullah, York University, Canada
Dr. Qin Xin, University of the Faroe Islands, Faroe Islands

Introduction
With recent technological advancement, humanity lives in the age of information. Digital progression revolutionized our everyday lives, and the most significant impact of digital rise is observed in the business world. The current environment of the business world is continuously evolving. This dynamic business environment is affected by various factors, including globalization, government policies, etc. Additionally, global economic growth in the business world provides significant challenges and opportunities like to survive in such a dynamic economy, and business environment decisions must be accurate and timely. Also, while making decisions, companies or organizations always need to be updated with the new business trend and economy to respond dynamically to customer needs and environmental changes. Business intelligence (BI) is a potential solution for efficient decision-making and profitable outcomes in the dynamic business world trends. A business intelligence framework allows a transformation of business data into valuable information, valuable information into in-depth knowledge, and knowledge into intelligent wisdom. Business intelligence(BI) can ultimately create an intelligent decision-making model with intellectual tactics, knowledge acquisition from recorded historical operational data. Smart business intelligence establishes a culture of business wisdom in the organization and distributes it to all organization users. With the capability of handling a dynamic business environment, more and more business organizations are moving towards BI. With global business expansion, business data received from diversified sources. The rapid development in business strategies leads to continuous enhancement in business data and information, forcing firms to gradually rely on external wisdom, knowledge, and intelligence for managing data to improve firm performance and move the business towards new innovative pathways. Earlier management of data information in the business world is accomplished using Data Warehousing and Data Mining techniques. These techniques enable business data with market intelligence to predict the future market trends and props market strategy to deal with the real-time business environment. However, BI with Data warehousing and Data mining enables the firms to understand consumer behavior and clues to predict future market trends only from two and Three-Dimensional views of Databases. With the development and implementation of artificial intelligence and big data technology in business, BI techniques can explore up to five-dimensional database view to analyze the market and predict the market's trading pattern. Big Data techniques with advanced AI capabilities in BI enable business organizations for accurately measuring the present and future perspectives from the past historical data. AI and big data technology allow BI to provide an effective decision-making model. However, BI still faces the challenge of coping with the intensive computing power and additional storage space required to handle this large sum of increasing data. This challenge can be addressed successfully by emerging technology cloud computing. With big data, AI, data science, and cloud computing BI is now an analytical and intelligent real-time model that enables the business world to predict consumer behavior and market trends.

Objective
The special issue entitled “Age of Information in Business Intelligence” focuses on implementing the latest technologies in the business world for effective decision-making strategies based on the historical age of information. We invite all the practitioners, researchers, and industry experts to submit their original research article that explores business intelligence technology to measure and analyze the present and future market trends based on past business records. The research paper may include data warehouses, data mining algorithms, big data, AI, and cloud computing technology to enable BI for effective decision-making.

Recommended Topics
• Reshaping business intelligence with data mining tactics • Towards the integration of data mining, AI, and big data in business intelligence • Application and implementation of data warehousing and data mining technology in predicting business world dynamics • Business analytics with big data and business intelligence with data mining for analyzing the historical age of business information • AI-assisted business intelligence with data warehouse and data mining approach • Data warehousing and mining (DWM) approach for digging out business intelligence with cloud computing storage and computing ability • DWM based business intelligence for effective decision-making process from the age of information. • Research on big data mining for e-commerce with Ai based business intelligence in a cloud environment • AI-assisted BI model implemented in a big data system embedding data mining • Challenges and opportunities for efficient decision making in the dynamic business world using the BI approach • Analysis of historical business data through BI assisted DWM techniques • Business intelligence framework in cloud environment using DWM and big data analytical approach

Submission Procedure
Researchers and practitioners are invited to submit papers for this special theme issue on Age of Information in Business Intelligence on or before November 11, 2021. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at http://www.igi-global.com/publish/contributor-resources/before-you-write/. All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.
November 11, 2021 - article submission deadline
Important Dates
February 28, 2022 - first notification deadline
April 30, 2022 - revised papers deadline
May 30, 2022 - final notification deadline