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Towards Generalizable Machine Learning Models For Computer-Aided Diagnosis In Medicine, Yiyang Wang
Towards Generalizable Machine Learning Models For Computer-Aided Diagnosis In Medicine, Yiyang Wang
College of Computing and Digital Media Dissertations
Hidden stratification represents a phenomenon in which a training dataset contains unlabeled (hidden) subsets of cases that may affect machine learning model performance. Machine learning models that ignore the hidden stratification phenomenon--despite promising overall performance measured as accuracy and sensitivity--often fail at predicting the low prevalence cases, but those cases remain important. In the medical domain, patients with diseases are often less common than healthy patients, and a misdiagnosis of a patient with a disease can have significant clinical impacts. Therefore, to build a robust and trustworthy CAD system and a reliable treatment effect prediction model, we cannot only pursue …
Empirical Assessment Of The Role Of Technology-Related Factors And Organization-Related Factors In Electronic Medical Records Implementation Success, Rangarajan Parthasarathy
Empirical Assessment Of The Role Of Technology-Related Factors And Organization-Related Factors In Electronic Medical Records Implementation Success, Rangarajan Parthasarathy
College of Computing and Digital Media Dissertations
The objective of this research was to investigate if certain technology-related and organization-related factors that have most often been associated with successful IT/MIS implementations in other information technology and information science domains are also associated with successful Electronic Medical Records (EMR) implementations. This research uncovered a unique set of technology-related factors and organization-related factors associated with successful EMR implementations from the perspective of healthcare enablers and healthcare providers. Specific technology-related factors considered in this research were the innovativeness of EMR (measured with respect to the relative advantage, compatibility and complexity of EMR), privacy and security attributes of EMR, and usefulness …