AIMC Topic: Diagnosis

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Generative transfer learning for measuring plausibility of EHR diagnosis records.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Due to a complex set of processes involved with the recording of health information in the Electronic Health Records (EHRs), the truthfulness of EHR diagnosis records is questionable. We present a computational approach to estimate the pro...

Building Bayesian Networks from Causal Rules.

Studies in health technology and informatics
Bayesian Networks (BNs) are often used for designing diagnosis decision support systems. They are a well-established method for reasoning under uncertainty and making inferences. But, eliciting the probabilities can be tedious and time-consuming espe...

Avoiding Overfitting in Deep Neural Networks for Clinical Opinions Generation from General Blood Test Results.

Studies in health technology and informatics
We have used deep neural networks (DNNs) to generate clinical opinions from general blood test results. DNNs have overfitting problem in general. We believe the complex structure of DNN and insufficient data to be the major reasons of overfitting in ...

A Semi-Automatic Framework to Identify Abnormal States in EHR Narratives.

Studies in health technology and informatics
Disease ontology, defined as a causal chain of abnormal states, is believed to be a valuable knowledge base in medical information systems. Automatic mapping between electronic health records (EHR) and disease ontology is indispensable for applying d...