Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics
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sg-smu-ink.sis_research-27292013-03-15T10:12:03Z Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics SEEMANTA, Khataniar MA, Nang Laik WU, Dan 2013-01-01T08:00:00Z text https://ink.library.smu.edu.sg/sis_research/1730 Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Health and Medical Administration Operations Research, Systems Engineering and Industrial Engineering |
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Artificial Intelligence and Robotics Health and Medical Administration Operations Research, Systems Engineering and Industrial Engineering |
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Artificial Intelligence and Robotics Health and Medical Administration Operations Research, Systems Engineering and Industrial Engineering SEEMANTA, Khataniar MA, Nang Laik WU, Dan Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
format |
text |
author |
SEEMANTA, Khataniar MA, Nang Laik WU, Dan |
author_facet |
SEEMANTA, Khataniar MA, Nang Laik WU, Dan |
author_sort |
SEEMANTA, Khataniar |
title |
Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
title_short |
Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
title_full |
Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
title_fullStr |
Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
title_full_unstemmed |
Using Predictive Analytics to predict “no show” patients contacted via SMS at specialist outpatient clinics |
title_sort |
using predictive analytics to predict “no show” patients contacted via sms at specialist outpatient clinics |
publisher |
Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/sis_research/1730 |
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