Réseau de l’ARC

Lisa Lix, Dr. Lisa Lix

Membre de :

Réseau de l’ARC

Téléphone : 204-789-3573

Adresse courriel lisa.lix@umanitoba.ca

Province : Manitoba

Affiliation : University of Manitoba

Institution: University of Manitoba

Languages: English (fluent spoken), English (fluent written)

Membre de :

Réseau de l’ARC

Téléphone : 204-789-3573

Adresse courriel lisa.lix@umanitoba.ca

Province : Manitoba

Affiliation : University of Manitoba

Institution: University of Manitoba

Languages: English (fluent spoken), English (fluent written)

Dr. Lisa Lix is a professor and associate head of Community Health Sciences at the University of Manitoba and currently serves on the board of directors of the Canadian Statistical Sciences Institute.

Dr. Lix is an internationally-recognized expert in the development and application of statistical models to improve chronic disease research and surveillance using population-based electronic health data. Her research has advanced scientific knowledge about bias in disease diagnoses, methods to improve validity of chronic disease case ascertainment methods, and chronic disease risk prediction.

As director of the Data Science Platform in the George & Fay Yee Centre for Healthcare Innovation, she oversees skilled biostatisticians, bioinformaticians, analysts and database developers who link and analyze clinical, administrative, and biological databases to strategically enhance the provincial and national environments for patient-focused research using electronic health data. She also leads nationally funded training initiatives on big data analytics and artificial intelligence in public/population health.

Site Web

Chercheur

University of Manitoba / Max Rady College of Medicine, Community Health Sciences, Room S113 - 750 Bannatyne Avenue, University of Manitoba Winnipeg, Manitoba R3E 0W3

Téléphone : 204-789-3573

Site Web

Régions:

  • Manitoba

Domaine d'intérêt

  • diagnostic techniques
  • health services
  • population and public health
  • secondary health data
  • statistics and inference

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