Advisory: Give yourself extra time when travelling by car to Toronto General Hospital, Princess Margaret Cancer Centre, or Toronto Rehab University Centre. City of Toronto construction on University Ave. may cause delays.
At UHN, we strive to deliver Compassionate Care & Caring. Learn more about the services and supports that are available to you throughout your journey.
Our UHN programs and services are among the most advanced in the world. We have grouped our physicians,
staff, services and resources into 10 medical programs to meet the needs of our patients and help us make
the most of our resources.
At the heart of everything we do at UHN are our Healthcare Professionals. Refer a patient to one of our 12 medical programs. Learn more about the resources and opportunities available for professional growth.
University Health Network has grown to be one of the largest research and teaching hospital networks in Canada - pioneers in improving the lives of patients. Our long history of health professions education at Toronto General, Toronto Western, Princess Margaret and Toronto Rehab hospitals has consistently advanced the science of education.
University Health Network is a health care and medical research organization in
Toronto, Ontario, Canada. The scope of research and complexity of cases at UHN has made us a national and international
source for discovery, education and patient care.
Being touched by illness affects us in different ways. Many people want to give back to the community
and help others. At UHN, we welcome your contribution and offer different ways you can help so you can find one that suits you.
The Newsroom is the source for media looking for information about UHN or trying to connect with one
of our experts for an interview. It's also the place to find UHN media policies and catch up on our news stories, videos, media releases,
podcasts and more.
Artificial Intelligence (AI) has blurred the lines between science fiction and reality with self-driving cars, humanoid robots, and virtual assistants. Recent progress in this technology has made Google Assistant's newest voice almost indistinguishable from a human's.
Researchers and companies are actively using AI to solve challenges in healthcare. Last month,
new work from
Dr. Babak Taati and his colleagues used deep learning, an area of AI, to help neurologists improve the treatment process for Parkinson's disease.
Individuals affected by Parkinson's disease can have reduced mobility and can experience loss of physical control. These symptoms worsen as the disease progresses. Although a cure does not currently exist, the severity of the symptoms can be reduced through medication or surgery.
A common medication for treatment is levodopa, a molecule that our body produces as part of normal function. Many patients who take this medication over long periods experience muscle spasms and involuntary movements.
Changing the dosage of the drug to reduce the symptoms of Parkinson's disease without causing spasms is difficult. Another challenge in evaluating these side effects is that the process is subjective and varies according to the particular experience of the specialist. Because of this, the specialist's assessment can differ considerably from what patients experience between visits.
To address this issue, Dr. Taati and his team captured series of short videos of patients after they received infusions of levodopa, and used the deep learning algorithm to track their body to measure the severity of the spasms and involuntary movements. The research team found that the AI algorithm performed as well or better than experienced neurologists.
"Our AI algorithm was able to objectively and accurately detect the onset and the remission of the spasms and involuntary movements and agreed with what the patients reported," explains Dr. Taati.
"Now that we know such an approach is feasible for Parkinson's disease, the next step is to validate it in more people and to improve the algorithm. The ultimate goal is to develop a clinical tool to help doctors design more effective treatments and minimize their side effects."
This work was supported by the Natural Sciences and Engineering Research Council of Canada, the Toronto Rehab Foundation, and the Toronto General & Western Hospital Foundation.