Digital Health Technologies (DHT)
The Institute for Management & Innovation (IMI) is proud to unveil a new concentration within the Master of Biotechnology for May 2019.
- Digital health introduction
- Three pillars of digital health
- What students will learn
- Requirements to apply
Digital Health Technologies (DHT) is a field of concentration within the Master of Biotechnology Program. DHT’s focus of training is data science and will include advanced training in machine learning tools. It is a two-year professional masters program that will involve eight months of placement in industry through paid student internships. Students will learn about basic business, health, regulation and data science.
The digital health field is diverse and includes: bio-physics, mobile medical apps, health information technology, general wellness, electronic medical records, software and cybersecurity, health information technology and wearable technology, to list a few. DHT is an area that invites a spectrum of expertise that goes beyond engineering and design.
The DHT field involves three main pillars:
- Health & Regulatory
- Data Science
Students will learn about chronic diseases, aging at home and health and wellness related issues including emerging technology. Regulation refers to privacy, data governance and policies set forth by the US Food and Drug Administration for the classification of medical products. Data science combines advanced statistical training with domain knowledge about healthcare and specific diseases. Students will be introduced to basic business concepts to understand profit drivers in this sector.
Students will complete eight months of industry internships in the Greater Toronto Area. Internships will draw upon the training students have received and will include relevant placements in this sector.
- A four year bachelor degree with a minimum “mid-B” (75 per cent average in the last two years of study).
- Degree program (or graduate degree) can be from a wide range of disciplines such as, not limited to: biology, public health, statistics, computer science, engineering, chemistry, engineering or epidemiology.
- Strong quantitative training. This can be illustrated by at least two courses in statistics, or by other courses with a strong focus on quantitative training (e.g., chemistry, population genetics, computer science, physics, econometrics).
- No prior knowledge of programming or business is assumed or required. Some exposure to life sciences is required.
Peter Munk donates historic $100 million to the Peter Munk Cardiac Centre, to lead in artificial intelligence and to revolutionize cardiovascular health care. Read more here.