Protecting Health Information. Ensuring Data Integrity.
Protecting Health Information. Ensuring Data Integrity.
EHIL Blog and Announcements
TMC AI Summit 2025 (February 20-21, 2025)
On February 21, Khaled El Emam will present the keynote address at the Texas Medical Center AI Summit 2025 in Houston, TX.
.png "Webinar: How Canadian Regulators Approach De-Identification: An Interview Study")
Webinar: How Canadian Regulators Approach De-Identification: An Interview Study
Lisa Pilgram and Khaled El Emam share the results of an interview study with Canadian privacy regulators to understand their perspectives on data anonymization.
Presentation at PHUSE Data Transparency Winter Event (4th February 2025)
EHIL Postdoctoral Fellow, Lisa Pilgram, will be presenting at the PHUSE Data Transparency Winter Event on February 4, 2025 on "Reducing Regulatory Uncertainty Around Anonymisation: Perspectives of Canadian Privacy Regulators".
IPC panel on The power of PETs: Privacy enhancing technologies (28 January 2025)
On January 28, join Khaled El Emam and an esteemed panel of experts to hear how PETs can be used in practice to support innovation while also protecting privacy.
Re-identification risk threshold literature review
A literature review on precedents for the threshold for re-identification risk.
Webinar: What not to do when publishing a machine learning modeling study
Dr. Khaled El Emam distills key learnings about publishing studies utilizing machine learning models.
Webinar: On the evaluation of synthetic data utility
On September 24, Dr. Fida Dankar presented her research work on synthetic data utility.
Webinar: Ethics of research involving humans in epidemiology and public health research
Do you conduct research involving human participants? Are you subject to the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS)? In this webinar, Hanan Abdel-Akher, Senior Policy Analyst with the Secretariat on Responsible Conduct of Research, answers these questions and more.
Webinar: Generating and Applying Synthetic Health Data
Synthetic data generation is an emerging approach for responsibly sharing data. Dr. Khaled El Emam reviews the use of generative models to produce synthetic real-world data and clinical trial data, along with studies evaluating the replicability of analyses using synthetic data and the privacy risks of synthetic data will. He also discusses further applications for enabling federated analysis and (selection) bias mitigation.
Webinar: The Utility Costs of Anonymization
On April 17, Lisa Pilgram presented an example application of anonymization in the field of nephrology. The focus was on utility and attention drawn to potential pitfalls. Video and slides available.
Webinar: Mitigating Bias in Real World Health Data
In February 2024, Lamin Juwara joined us to discuss the results of his recently published study “An evaluation of synthetic data augmentation for mitigating covariate bias in health data” on bias mitigation techniques to correct biased datasets. Webinar video available at: https://vimeo.com/918399218
Release of machine learning R package (experimental)
This is the release announcement for the sdgm R package. This is the package we use on our intro to machine learning class.