Machine learning-enabled healthcare information systems in view of Industrial Information Integration Engineering
Özet
Recent studies on Machine learning (ML) and its industrial applications report that ML-enabled systems may be at a high risk of failure or they can easily fall short of business objectives. Cutting-edge developments in this field have increased complexity and also brought new challenges for enterprise information integration. This situation can even get worse when considering the vital importance of ML-enabled healthcare information systems (HEIS). Therefore, the main argument of this paper is that we need to adopt the principles of Industrial Information Integration Engineering (IIIE) for the design, development, and deployment processes of ML-enabled systems. A mixed research paradigm is adopted, and therefore, this study is conducted by following the guidelines and principles of Action Research, Design Science Research, and IIIE. The contributions of this study are two-fold: (a) to draw researchers' and practitioners' attention to the integration problems of ML-enabled systems and discuss them in view of IIIE, and (b) to propose an enterprise integration architecture for ML-enabled HEIS of a uni-versity hospital, which is designed and developed by following the guidelines and principles of IIIE.
Bağlantı
http://hdl.handle.net/11727/8443Koleksiyonlar
İlgili Öğeler
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
-
Online students' LMS activities and their effect on engagement, information literacy and academic performance
Avci, Ummuhan; Ergun, Esin (2019)The purpose of this study was to examine online students' LMS activities and the effect on their engagement, information literacy, and academic performance. The participants of the study were 65 undergraduate students ... -
SOURCES THAT MANAGERS PREFER FOR BUSINESS INFORMATION NEEDS
Baskici, Cigdem (2019)This study aims to reveal how business managers associate their information needs and the information sources to meet these needs. In order to answer this question, face-to-face interviews were carried out with a total of ... -
Turkish cancer patients' preference for information and communication technologies
Ildes, E.; Eser, A. Karaslan; Gokdag, S. T. (2019)