People of Sinai Health: Dr. Masoom Haider, Head of Radiomics and Machine Learning Imaging ... .

Mount Sinai Hospital, New York

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Masoom Haider POSH

Artificial intelligence (AI) is an emerging new field that is being incorporated into video games, self-driving cars, mobile devices, online shopping, and much more. AI’s many life-changing applications range from entertainment to transportation, from communication to consumption. As scientists around the world are starting to harness the power of AI to improve people’s health, Sinai Health System aims to be on the leading edge of this emerging field.

We sat down with Dr. Masoom Haider from the department of medical imaging to learn more about the innovative work and how machine learning, which is a subset of artificial intelligence, has the potential to make advances in the diagnosis and treatment of cancer.

Tell us about your role.

In our lab, we mine information in MRI and CT scans using fast computers with gaming hardware that learn from experience – popularly called artificial intelligence (AI) – to help find cancers and determine how aggressive they are. AI enhances our ability to do this, instead of relying on human interpretation alone.

How did you get into the field?

I actually wanted to become a computer scientist but I found medical imaging as a medical specialty and discovered how it combined computers, technology and patient care. I was hooked.

What made you want to work at Sinai Health?

I joined Sinai Health in January 2018. I was attracted by the opportunity to take on a Clinician-Scientist position within the institution that allowed me to focus on research. Research has always been my first love and I wanted to work for an organization that would invest and believe in my work. I was also attracted to the inclusivity and diversity at the organization.

What does a typical day look like for you?

I report MRI and CT scans of patients with cancer, Crohn’s disease and other diseases of the abdomen and pelvis a few days a week. I also direct our lab and conduct research with a team of outstanding engineers, computer scientists, graduate students and budding clinician scientists who want to learn more about machine learning and AI.

What opportunities do you think will come from machine learning that you’re most optimistic about? What challenges or repercussions of this change are you concerned about?

I think there’s a huge opportunity to make advances in diagnosis and treatment of cancers by using machine learning, which is a subset of AI. Machine learning is when a computer learns through experience how to identify cancers – so, the more data it looks at, the better it gets at predicting cancers and their implications for a patient. It also allows us to process more data at a much quicker rate and without human error. On the flip side, there are also challenges associated with machine learning. Access to data, ethical issues of who is responsible for errors made by the machine, avoiding biases by including ethnically diverse populations and so on. Toronto has world leaders in the field and many groups are coming together for the first time to overcome these challenges. In the end we envision AI, doctors and their patients working together to make the best care decisions for their personal health.

Tell us about an achievement you’re most proud of.

I’m most proud of work that has an impact on patients. One of my greatest achievements was to help bring new techniques using MRI to find hidden prostate cancers and be one of the first to bring this to Canadian patients.

What’s your favourite part of the day?

I love interacting with the students and research fellows in the lab. Many of them come from all across the world to study and train in Toronto and offer unique perspectives.

What’s your personal mantra?

“Be a life-long student.”