Public universities employees perception of electronic information sharing between universities and the Ministry of Higher Education and Scientific Research

Electronic information sharing benefits organizations and institutions in various aspects including increasing the level of information accuracy and timeliness, improving the accountability and decision making, and minimizing the cost of information management. There is a high degree of information sharing between Iraqi public universities and Ministry of Higher Education and Scientific Research (MOHESR), however, limited electronic information sharing exists between them, which brings difficulties and delay in making decisions. This limitation also creates challenges and barriers in supporting the decentralization principle taken by the public universities in universities’ governance. Thus, there is a need to conduct a study to identify the possible steps and strategies to increase electronic information sharing between the ministry and universities. The main objective of this study is to propose a model of electronic information sharing between Iraqi public universities and MOHESR. Social Exchange Theory, Critical Mass Theory and Transactive Memory System Theory have been used to solve the problem and achieve the objectives. Purposive sampling has been used and multiple linear regression analyses were applied for data analysis. A total of 660 questionnaires have been distributed in five universities in Iraq and the returned response was 274 (42%). From the 16 factors proposed, ten factors are found to be significance which are IT capability, information quality, compatibility, complexity, data warehouse, top management, policy/legal framework, interagency trust, upper level leadership and social network. Based on the results obtained, the study presents a model of electronic information sharing between public universities in Iraq and MOHESR. A comprehensive understanding of this model will contribute to the improvement of the planning and implementation of three dimensions; technological, organizational and environmental of the public universities in their way forward to improvise electronic information sharing in the future. According to the findings, it can be concluded that three dimensions and ten factors can essentially increase the electronic information sharing among public universities and MOHESR

Medical Informatics

Information technology has been revolutionizing the everyday life of the common man, while medical science has been making rapid strides in understanding disease mechanisms, developing diagnostic techniques and effecting successful treatment regimen, even for those cases which would have been classified as a poor prognosis a decade earlier. The confluence of information technology and biomedicine has brought into its ambit additional dimensions of computerized databases for patient conditions, revolutionizing the way health care and patient information is recorded, processed, interpreted and utilized for improving the quality of life. This book consists of seven chapters dealing with the three primary issues of medical information acquisition from a patient's and health care professional's perspective, translational approaches from a researcher's point of view, and finally the application potential as required by the clinicians/physician. The book covers modern issues in Information Technology, Bioinformatics Methods and Clinical Applications. The chapters describe the basic process of acquisition of information in a health system, recent technological developments in biomedicine and the realistic evaluation of medical informatics

Disruptive Technologies as a Driver to Organizational Success. Organizational Culture Perspective

There is a lot of evidence in the research literature that Information Technologies can play a crucial role in achieving competitive advantage, improving decision-making, and achieving organizational success. Unfortunately, research on exploring the issues of using Disruptive Technologies (DT) is still limited, especially studies into the relationship between the use of DT and organizational success. The main contribution of this study is to investigate the issue of DT's impact on organizational success, in particular identifying the benefits of using DT in organizations, as well as examining to what extent organizational culture can be a factor in enhancing organizational success. The study presents the results of research on the use of Disruptive Technologies carried out in 194 organizations, especially in the areas of DT usage and the benefits that organizations achieve from adopting them, as well as the impact of organizational culture on organizational success

Empirical investigation of decision tree ensembles for monitoring cardiac complications of diabetes

Cardiac complications of diabetes require continuous monitoring since they may lead to increased morbidity or sudden death of patients. In order to monitor clinical complications of diabetes using wearable sensors, a small set of features have to be identified and effective algorithms for their processing need to be investigated. This article focuses on detecting and monitoring cardiac autonomic neuropathy (CAN) in diabetes patients. The authors investigate and compare the effectiveness of classifiers based on the following decision trees: ADTree, J48, NBTree, RandomTree, REPTree, and SimpleCart. The authors perform a thorough study comparing these decision trees as well as several decision tree ensembles created by applying the following ensemble methods: AdaBoost, Bagging, Dagging, Decorate, Grading, MultiBoost, Stacking, and two multi-level combinations of AdaBoost and MultiBoost with Bagging for the processing of data from diabetes patients for pervasive health monitoring of CAN. This paper concentrates on the particular task of applying decision tree ensembles for the detection and monitoring of cardiac autonomic neuropathy using these features. Experimental outcomes presented here show that the authors' application of the decision tree ensembles for the detection and monitoring of CAN in diabetes patients achieved better performance parameters compared with the results obtained previously in the literature

LEVERAGING IN-MEMORY TECHNOLOGY TO IMPROVE THE ACCEPTANCE OF MSS - A MANAGERS´ PERSPECTIVE

Management support systems (MSS) help managers to perform their jobs more efficiently. With in-memory technology, a new IT enabler promises to support managers by benefits ranging from reducing time for MSS data entry and analysis to completing even new topics of analysis. Hence, the present situation is favorable for an MSS redesign applying in-memory apps. Such apps are field-tested and ready-to-use, but from a business perspective they lack impact. Based on findings from a literature review and results from a workshop with an expert focus group validated with one-on-one manager interviews, we propose four initial use situations in which in-memory apps contribute to greater MSS acceptance: (1) In-memory apps should accelerate the MSS response time for both check status and receive an alert. In doing so, they should focus on information from management accounting. (2) By delivering information more timely, in-memory apps should contribute to MSS standard reports and financial closing. (3) In-memory apps should accelerate MSS response time for both ad-hoc analysis and drill-down/drill-through analysis. (4) Leveraging in-memory apps, MSS ad-hoc analysis and drill down/drill-through analysis should become more flexible.

Clinical Decision Support System for Unani Medicine Practitioners

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.Comment: 59 pages, 11 figures, Computer Science Bachelor's Thesis on use of Artificial Intelligence in Clinical Decision Support System for Unani Medicine

Transactions of 2015 International Conference on Health Information Technology Advancement Vol.3, No. 1

The Third International Conference on Health Information Technology Advancement Kalamazoo, Michigan, October 30-31, 2015 Conference Chair Bernard Han, Ph.D., HIT Pro Department of Business Information Systems Haworth College of Business Western Michigan University Kalamazoo, MI 49008 Transactions Editor Dr. Huei Lee, Professor Department of Computer Information Systems Eastern Michigan University Ypsilanti, MI 48197 Volume 3, No. 1 Hosted by The Center for Health Information Technology Advancement, WM

New Fundamental Technologies in Data Mining

The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining