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Welcome to the Electronic Health Information Laboratory website!
To find out more about Khaled El Emam, the lab's senior investigator,
click here.
To find out more about what we do, click here.
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Magnitude and Impact of Hallucinations in Tabular Synthetic Health Data on Prognostic Machine Learning Models
Read our paper investigating the magnitude and impact of hallucinations in tabular synthetic data recently published in JMIR.
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Augmenting Insufficiently Accruing Oncology Clinical Trials Using Generative Models
This paper provides a comprehensive evaluation on the extent generative models can be used to simulate additional patients to compensate for insufficient accrual in clinical trials.
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Recording Available for A Consensus Privacy Metrics Framework for Synthetic Data Webinar
See Lisa Pilgram's presentation and read our newly published paper on the topic in Patterns.
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Applying Machine Learning to Predict Complex Clinical Course in Youth With Eating Disorders
This paper compares the predictive performance of supervised machine learning models to logistic regression in identifying youth with eating disorders at risk of a complex clinical course.
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