| Tuesday, May 14, 2024,
15:00-16:00 |
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The
Health AI and Data Science (HAD)
Program presents
TBD
| Speaker:
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Gauruv Bose
Dr. Gauruv Bose is full-time academic neurologist at the Ottawa Hospital, Department of Medicine, Division of Neurology, and assistant professor at the University of Ottawa, Faculty of Medicine. He completed a Clinical Research Fellow in Multiple Sclerosis and Neuroimmunology at Mass General Brigham & Harvard Medical School, and is now primarily seeing patients with Multiple Sclerosis and related neuro-immunological disorders.
His research consists of investigating large real-world datasets of patients with Multiple Sclerosis (MS) to develop predictive models using machine learning techniques, as well as building on this research forefront by investigating the added value of implementing novel imaging and serum biomarkers into these predictive models.
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| Location:
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Virtual via MS Teams. Meeting ID: 267 677 792 865 | Passcode: aoyqYp
Please contact Emma Brown at emmabrown1@ohri.ca if you would like the meeting link.
NOTE: If you would like to be added to the HAD - Health AI and Data Science team on MS Teams (including the HAD JC seminar mailing list), please join the team using code: owfh55e. If you are external to TOH/OHRI and would like to be added, please email Emma Brown at emmabrown1@ohri.ca.
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More details to come.
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| Tuesday, May 28, 2024,
15:00-16:00 |
|
The
Health AI and Data Science (HAD)
Program presents
Developing and Deploying Transparent and Reproducible Predictive Algorithms in Healthcare (Part 2 of 2)
| Speaker:
|
Juan Li and Kitty Chen
Juan Li is a Senior Clinical Research Associate in Neuroscience Program and Clinical Epidemiology Program at OHRI. Her main research interest includes predictive modelling, risk of Parkinson disease, machine learning, clinical research, and psychometrics.
Kitty Chen is a research assistant at the Ottawa Hospital Research Institute, with an MPH in epidemiology from the University of Toronto. She has been involved in several projects related to chronic diseases using big data and has a strong interest in open science.
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| Location:
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Virtual via MS Teams. Meeting ID: 256 113 661 42 | Passcode: dThgeo
Please contact Emma Brown at emmabrown1@ohri.ca if you would like the meeting link.
NOTE: If you would like to be added to the HAD - Health AI and Data Science team on MS Teams (including the HAD JC seminar mailing list), please join the team using code: owfh55e. If you are external to TOH/OHRI and would like to be added, please email Emma Brown at emmabrown1@ohri.ca.
|
This is a two-part seminar series. Part 1 of the seminar series will be held on April 16th by Doug Manuel and Wenshan Li from the Ottawa Hospital Research Institute. A recording of Part 1 will be available in the HAD JC MS Teams channel. If you would like to view the recording and do not have access, please email emmabrown1@ohri.ca to receive the link.
Learning Objectives:
By the end of the sessions, participants will:
- Be able to apply open science principles in developing predictive algorithms to enhance reproducible science and improve patient care quality
- Understand the approaches used by other participants, thereby improving researcher and IS collaboration for algorithm development and deployment
Part 1 – Foundations for reproducible predictive algorithms in healthcare
Objectives: review and discuss the essentials of reproducible and transparent AI, understanding its imperatives, best practices, and challenges in the healthcare context.
- Review and discuss open science from the perspective of predictive algorithms in health care.
- Examine case studies comparing open-source and proprietary workflows in algorithm development, discussing their implications for healthcare IT and patient care.
Part 2 – Practical application of open and reproducible predictive algorithms
Objectives: Engage in hands-on development and deployment of predictive algorithms using open-source tools, with a focus on real-world healthcare applications.
- Review a hands-on example of algorithm development and deployment using an open-source workflow (R Tidymodels and Plumber).
- Walk-through of algorithm development and deployment at the Project Big Life platform.
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| Tuesday, June 11, 2024,
15:00-16:00 |
|
The
Health AI and Data Science (HAD)
Program presents
TBD: Large Language Models Seminar Presentation (Part 1 of 2)
| Speaker:
|
Arya Rahgozar, Doug Manuel, and Juan Li
Arya Rahgozar, PhD is an adjunct professor of Data Science at Faculty of Engineering and postdoctoral fellow at the Department of Family Medicine, University of Ottawa. Arya did his master’s in management sciences, at the University of Waterloo. Arya''''''''s background is in applied mathematics and computer science with the focus on NLP and its applications in medicine.
Dr. Doug Manuel holds the position of Senior Scientist at the Ottawa Hospital Research Institute and is a distinguished professor at uOttawa’s Department of Family Medicine and School of Epidemiology and Public Health, holding a Tier 1 Clinical Research Chair in Precision Medicine for Disease Prevention. Dr. Manuel holds an additional appointment as a senior investigator at Bruyère Research Institute.
Dr. Manuel’s research combines expertise in public health, healthcare systems, and primary care, focusing on understanding factors contributing to differences in population health outcomes across societies. This research involves developing and using advanced predictive algorithms and microsimulation models to assess the potential impact of health interventions and policy strategies. Dr. Manuel collaborates on Project Big Life, a website with disease risk calculators, helping millions globally to understand their health and contribute to evidence-based public health decisions.
Juan Li is a Senior Clinical Research Associate in Neuroscience Program and Clinical Epidemiology Program at OHRI. Her main research interest includes predictive modelling, risk of Parkinson disease, machine learning, clinical research, and psychometrics.
|
| Location:
|
Virtual via MS Teams. Meeting ID: 221 062 051 071 | Passcode: TAHMTr
Please contact Emma Brown at emmabrown1@ohri.ca if you would like the meeting link.
NOTE: If you would like to be added to the HAD - Health AI and Data Science team on MS Teams (including the HAD JC seminar mailing list), please join the team using code: owfh55e. If you are external to TOH/OHRI and would like to be added, please email Emma Brown at emmabrown1@ohri.ca.
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More details to come.
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| Tuesday, June 25, 2024,
15:00-16:00 |
|
The
Health AI and Data Science (HAD)
Program presents
TBD: Large Language Models Seminar Presentation (Part 2 of 2)
| Speaker:
|
Arya Rahgozar, Doug Manuel, and Juan Li
Arya Rahgozar, PhD is an adjunct professor of Data Science at Faculty of Engineering and postdoctoral fellow at the Department of Family Medicine, University of Ottawa. Arya did his master’s in management sciences, at the University of Waterloo. Arya''''''''s background is in applied mathematics and computer science with the focus on NLP and its applications in medicine.
Dr. Doug Manuel holds the position of Senior Scientist at the Ottawa Hospital Research Institute and is a distinguished professor at uOttawa’s Department of Family Medicine and School of Epidemiology and Public Health, holding a Tier 1 Clinical Research Chair in Precision Medicine for Disease Prevention. Dr. Manuel holds an additional appointment as a senior investigator at Bruyère Research Institute.
Dr. Manuel’s research combines expertise in public health, healthcare systems, and primary care, focusing on understanding factors contributing to differences in population health outcomes across societies. This research involves developing and using advanced predictive algorithms and microsimulation models to assess the potential impact of health interventions and policy strategies. Dr. Manuel collaborates on Project Big Life, a website with disease risk calculators, helping millions globally to understand their health and contribute to evidence-based public health decisions.
Juan Li is a Senior Clinical Research Associate in Neuroscience Program and Clinical Epidemiology Program at OHRI. Her main research interest includes predictive modelling, risk of Parkinson disease, machine learning, clinical research, and psychometrics.
|
| Location:
|
Virtual via MS Teams. Meeting ID: 298 473 539 616 | Passcode: iQ262y
Please contact Emma Brown at emmabrown1@ohri.ca if you would like the meeting link.
NOTE: If you would like to be added to the HAD - Health AI and Data Science team on MS Teams (including the HAD JC seminar mailing list), please join the team using code: owfh55e. If you are external to TOH/OHRI and would like to be added, please email Emma Brown at emmabrown1@ohri.ca.
|
More details to come.
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