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Artificial Intelligence in Cancer Care

We support expertise in artificial intelligence (AI) and oncology in Quebec through an active community of practice who seeks to improve care for people with cancer and their loved ones.
AI’s potential in oncology is huge, especially in terms of cancer prevention and detection and the personalization of cancer treatments. AI can improve the efficiency and quality of care and increase the odds of saving lives. At the Canadian Cancer Society, we invest in cutting-edge research to stimulate innovations for the benefit of people with cancer and their loved ones.

To integrate these technologies into everyday care pathways, it is essential that people understand AI and what it can concretely change in the oncology field. With the support of the Quebec Ministère de l’Économie, de l’Innovation et de l’Énergie (MEIE), the Canadian Cancer Society and the CHUM School of Artificial Intelligence in Healthcare (ÉIAS) developed a program to promote AI-oncology pioneers in Quebec and to give health professionals and people living with cancer the tools they need to use these new technologies.

The Impact of AI - Three major use cases in Quebec

[Stéphanie Thibaudeau is seated in a waiting room facing the camera.]

Stéphanie Thibaudeau: When you’re diagnosed with cancer, you obviously want to survive. You want to optimize your chances of completely irradiating the cancer.

[The image fades and the screen turns blue.]

Text on screen: Treating cancer using artificial intelligence

[Dr Tsui is standing in a hospital corridor, speaking into the camera]

Text on screen: Dr Tsui, Radiation Oncologist and Researcher at the MUHC

Dr Tsui: What can artificial intelligence do?

[Dr Tsui is seated at a computer, pointing to a pelvic x-ray image on the screen.]

It's about automatically auto-segmenting, auto-contouring, auto-drawing all of these organs.

[Dr Tsui is standing in front of camera.]

Dr Tsui: So the advantage is that instead of hours of work, it only takes a fraction of that time.

[Dr Tsui and a colleague examine X-ray sections on the computer.]

Stéphanie Thibaudeau: In my case, it’s the pelvic region.

[Stéphanie Thibaudeau, seated, facing the camera]

Text on screen: Stéphanie Thibaudeau, Patient of Dr Tsui

Stéphanie Thibaudeau: There are many organs, the intestines, the bladder. Talking to Dr Tsui really reassured me.

[Stéphanie Thibaudeau is talking to Dr Tsui in a consultation room, then faces the camera again]

Stéphanie Thibaudeau: I really trusted that the treatment plan was personalized, that we were really trying to optimize the radiation area without affecting my other organs.

[Technologists prepare a radiotherapy machine.]

Dr Tsui: So all of this frees up resources and allows us to treat more patients.

[Views of the facade of the Centre hospitalier de l’Université de Montréal followed by the reception of the Department of Radiation Oncology.]

Raphaèle Piot-Rolland: We treat around 100 patients a day in the Oncology Department alone.

[Raphaèle Piot-Rolland is seated, facing the camera]

Text on screen: Raphaèle Piot-Rolland, Vice President, Operations, Gray Oncology Solutions

Raphaèle Piot-Rolland: The solution used to be someone having to figure out this Tetris puzzle every day.

And now they can press on a button and in five minutes, it’s done, and they can adapt the program based on their knowledge...

[An employee of the Department of Radiation Oncology at the CHUM is seated in front of a computer that shows Gray's software.]

Raphaèle Piot-Rolland: We developed a program called Gray with the CHUM...

[Raphaèle Piot-Rolland speaks into the camera. The next shot shows Raphaèle sitting at her desk in front of her computer, browsing Gray's software.]

Raphaèle Piot-Rolland: ...which can automate, optimize and coordinate the care pathways of patients and, more specifically, how their appointments are managed.

[Raphaèle Piot-Rolland, seated, facing the camera]

AI can help us on two fronts.

Raphaèle Piot-Rolland: First, it allows us to optimize schedules, that is to say, optimize the use of hospital resources and reduce patient wait times.

[Two radiation oncology employees consult an appointment calendar together on Gray’s software.]

[Raphaèle Piot-Rolland, seated, facing the camera.]

Raphaèle Piot-Rolland: Second, AI can predict cancellations and patient volumes so we can make better decisions.

[Comings and goings of passers-by in a CHUM corridor.]

[The visual changes. Steve Bondu, seated, speaks into the camera.]

Text on screen: Steve Bondu, CHUM patient

Steve Bondu: The logistics here at the CHUM amaze me every day. I'm undergoing radiotherapy, so I’m able to get my treatment and then go to another floor for the appointment I have 10 minutes later.

[Two technologists help Steve Bondu lie down on the radiotherapy machine.]

Steve Bondu: They’ll say to me “Mr. Bondu, we’ve been waiting for you.” Things are hopping here, but with a logistical finesse that’s good for patients.

[Dr Bahig, seated, speaks into the camera.]

Text on screen: Dr Houda Bahig, Radiation Oncologist and Researcher at the CHUM

Dr Bahig: So the project we’re working on is one intended to individualize radiotherapy treatments for head and neck cancers.

[Steve Bondu is lying on the radiotherapy machine. He’s wearing a plastic mask from the top of his head to his neck, and beams are passing over him.]

[There are computer screens in the control room during his radiotherapy treatment.]

Dr Bahig: The goal of this project is to try to analyze the images of patients taken every day over seven weeks of treatment…

[Dr Bahig, seated, facing the camera. The next visual shows Dr Bahig during a follow-up appointment with Steve Bondu.]

Dr Bahig: and to analyze their clinical data to try to predict which patients will respond more quickly to treatments and which patients will have more serious side effects.

[Samuel Kadoury, seated, speaks into the camera.]

Text on screen: Samuel Kadoury, Professor at École polytechnique, Researcher at the CHUM

Samuel Kadoury: We’re currently training the model with more than a thousand cases. We always try to have an updated model with as much data as is available. The tool will always seek to complement the doctor’s work.

[Dr Bahig and Samuel Kadoury are seated in front of a laptop and talking as they examine x-rays.]

[Technologists finish setting Steve Bondu up on the radiotherapy machine. The video ends with Dr Bahig speaking into the camera.]

Dr Bahig: Through the discoveries it allows us to make, artificial intelligence will really be able to help us improve patient care pathways while making treatments more effective.

[The screen fades to black.]

Text on screen: AI has the potential to improve the care and lives of people with cancer.

Text on screen:

Special thanks to:

Dr James Tsui – Stéphanie Thibaudeau - Raphaèle Piot-Rolland - Steve Bondu – Dr Houda Bahig - Samuel Kadoury, Ph. D. - The Oncology and Radiation Oncology Department teams at the CHUM - The Cedars Cancer Center teams at the MUHC.

Science and Andragogy Committee of the program:

Dr An Tang - Dr Houda Bahig – Natalie Mayerhofer - Christian Blouin, patient partner at the CHUM

[The logos of the Canadian Cancer Society, the CHUM School of Artificial Intelligence in Health and the Government of Quebec appear onscreen.]

A group of AI-Oncology attendees

AI-Oncology community

We have developed a learning pathway for Quebec AI experts in oncology so they can hone their ability to pass on their know-how to their peers, to medical teams, and to people living with cancer.

The “AI-Oncology Training Day: share your knowledge with impact” held in November 2023 during a symposium about AI in healthcare enabled participants to experiment with learning methods adapted to their needs.

A community of experts in AI and oncology was launched to stimulate collaboration between researchers, clinicians, entrepreneurs and patient partners and continue to equip them to effectively pass on their AI knowledge.

A group of AI-Oncology attendees

Our tools to understand AI

Discover our series of training activities and content to help healthcare professionals and people living with cancer better understand AI and its usefulness for cancer detection, diagnosis and care.

The IA et Oncologie podcast (AI and Oncology, in French only) presents the stories of specialists, caregivers and patient partners. They discuss issues with the cancer care pathway and the solutions AI offers to better support people affected by cancer.
Our educational kit, offered only in French, provides keys to understanding what AI is. It explains how this new technology can help prevent cancer and make a difference for people affected by cancer at every stage of the care pathway. 

Mapping AI and Oncology Projects in Quebec

This guide lists laboratories, research projects and entrepreneurial initiatives combining AI and oncology. A growing innovation ecosystem in Quebec!

To learn more, contact Julia Nordlund (julia.nordlund@cancer.ca).

This program is organized by the Canadian Cancer Society and the CHUM School of Artificial Intelligence in Healthcare, with the financial support of the Quebec Ministère de l’Économie, de l’Innovation et de l’Énergie (MEIE).


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