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Success factors for national eHealth strategies: a comparative analysis of the Australian and German eHealth system.

, , , and . Int. J. Netw. Virtual Organisations, 21 (4): 399-424 (2019)

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Predictive analytics of readmission risk in hospitals for an intelligent decision support system.. University of Erlangen-Nuremberg, Germany, (2021)Mining Customer Satisfaction on B2B Online Platforms using Service Quality and Web Usage Metrics., , , , , and . APSEC, page 435-444. IEEE, (2020)Success factors for national eHealth strategies: a comparative analysis of the Australian and German eHealth system., , , and . Int. J. Netw. Virtual Organisations, 21 (4): 399-424 (2019)Readmission risk prediction for patients after total hip or knee arthroplasty., , , and . ACIS, page 87. (2017)Decision Support for Patient Discharge in Hospitals - Analyzing the Relationship Between Length of Stay and Readmission Risk, Cost, and Profit., and . SERVICES, volume 12411 of Lecture Notes in Computer Science, page 77-84. Springer, (2020)Using Collective Intelligence to Generate Trend-based Travel Recommendations., , and . KDIR, page 177-185. SciTePress, (2015)Development and evaluation of ensemble-based classification models for predicting unplanned hospital readmissions after hysterectomy., , and . ACIS, page 62. (2018)A theoretical framework for research on readmission risk prediction., , and . Bled eConference, page 40. University of Maribor Press / Association for Information Systems, (2019)An Intelligent Clinical Decision Support System to Determine the Optimal Time of Patient Discharge in Hospitals., and . ICIS, Association for Information Systems, (2020)Initial Phase of Developing a Model to Predict Unplanned Readmissions in the Australian Private Healthcare Sector before they Occur: the Case of Hysterectomy., , , , and . AMIA, AMIA, (2019)