Faculty
Schulich School of Medicine & Dentistry
Supervisor Name
Greg Zaric
Keywords
machine learning, reporting standards, type 2 diabetes, TRIPOD, MI-CLAIM, DOME
Description
In this project, three people scored 90 papers on machine learning predictive models for type 2 diabetes to assess their adherence to TRIPOD, MI-CLAIM, and DOME reporting guidelines.
Acknowledgements
Thank you to Dr. Greg Zaric, Dr. Yang Li, the Western USRI program, and the Schulich School of Medicine & Dentistry for their support.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Document Type
Poster
Included in
Artificial Intelligence and Robotics Commons, Endocrinology, Diabetes, and Metabolism Commons
Reporting Standards for Machine Learning Research in Type 2 Diabetes
In this project, three people scored 90 papers on machine learning predictive models for type 2 diabetes to assess their adherence to TRIPOD, MI-CLAIM, and DOME reporting guidelines.