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GTC ON-DEMAND

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Abstract:
We'll talk about health care deep learning initiatives we're pursuing to better serve our patients. These include improving the process of prior authorization, which is not only costly, but takes time that can affect patients' conditions and customer satisfaction. We'll discuss how we're applying deep learning to enable real-time processing of prior authorizations. We'll cover how we're using deep learning to more effectively detect medical claims fraud. Instead of traditional unsupervised outlier detection, deep learning can predict the provider or member's unique features, and use those to detect abnormal medical claims and reduce false positives. And we'll also explain how we're using deep learning for multiple disease imputation and prediction. Based on a patient's historical EHR, we can accurately impute multiple medical conditions as well as predict future conditions with an eye toward intervention.
We'll talk about health care deep learning initiatives we're pursuing to better serve our patients. These include improving the process of prior authorization, which is not only costly, but takes time that can affect patients' conditions and customer satisfaction. We'll discuss how we're applying deep learning to enable real-time processing of prior authorizations. We'll cover how we're using deep learning to more effectively detect medical claims fraud. Instead of traditional unsupervised outlier detection, deep learning can predict the provider or member's unique features, and use those to detect abnormal medical claims and reduce false positives. And we'll also explain how we're using deep learning for multiple disease imputation and prediction. Based on a patient's historical EHR, we can accurately impute multiple medical conditions as well as predict future conditions with an eye toward intervention.  Back
 
Topics:
Medical Imaging & Radiology, AI & Deep Learning Research
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9399
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Abstract:
We'll present a use case of applying machine learning and deep learning to the task of imputing/predicting a medical patient diagnosis based on data elements of their member, medical, and pharmacy claims. We'll introduce deep learning approaches, a side by side comparison of machine learning models vs. deep learning models, and illustrate the operation and business value of deep learning models.
We'll present a use case of applying machine learning and deep learning to the task of imputing/predicting a medical patient diagnosis based on data elements of their member, medical, and pharmacy claims. We'll introduce deep learning approaches, a side by side comparison of machine learning models vs. deep learning models, and illustrate the operation and business value of deep learning models.  Back
 
Topics:
AI in Healthcare, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Washington D.C.
Year:
2017
Session ID:
DC7154
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