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Research Article 2023CC BYFree full text

Prediction of Adverse Events Risk in Patients with Comorbid Post- Traumatic Stress Disorder and Alcohol Use Disorder Using Electronic Medical Records by Deep Learning Models

Oshin Miranda, Peihao Fan, Xiguang Qi, Haohan Wang, M Daniel Brannock, Thomas Kosten +3 more

Abstract Background Prediction of high-risk events in mental disorder patients is crucial. In our previous study, we developed a deep learning model: DeepBiomarker by using electronic medical records (EMR) to predict suicide related event (SRE) risk in post-traumatic stress disorder (PTSD) patients. Methods We applied DeepBiomarker2 through data integration of multimodal information: lab test, medication, co-morbi…

Research Square PubMed Central Open Access

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Research Article 2018-10-13CC BY-NCFree full text · non-commercial reuse

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications

Haohan Wang, Zhenglin Wu, Eric P. Xing

The proliferation of healthcare data has brought the opportunities of applying data-driven approaches, such as machine learning methods, to assist diagnosis. Recently, many deep learning methods have been shown with impressive successes in predicting disease status with raw input data. However, the \"black-box\" nature of deep learning and the high-reliability requirement of biomedical applications have created ne…

bioRxiv bioRxiv

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