Hello BRIGHT Run Family,
Happy November!
I am having a happily busy fall term.
I presented a bootcamp session on Artificial Intelligence (AI) at the Master of Biomedical Innovation (MBI) program in McMaster University’s Heersink School of Biomedical Innovation and Entrepreneurship in late September. This program includes students who are interested in the transfer of biomedical technologies for commercialization.
I also worked with some of my colleagues on developing and submitting a grant proposal on breast cancer imaging.
Part of my work includes preparing and revising manuscripts. This happens when you try to publish your research in a journal. You begin with your research question, gather your data, perform analysis/experiments, and draw your conclusions. This is a rigorous process that takes time to get to the finishing point.
Then you (and members of your team involved in the work) write about your research and findings in a scholarly manner so that you can send it for peer review by submitting your paper to a journal.
If the journal’s editorial team finds your paper meets their scope and other requirements, they invite peer reviewers for your work. The peer reviewers read, provide feedback, and critique your paper scientifically.
Then the editorial team decides whether to give authors a chance to respond to the peer reviewers. This stage is called ‘revision’. After revision, you re-submit your paper to the same editorial team, and they usually send it back to the reviewers for the second round of review.
If the reviewers are satisfied by your responses, the paper is likely to be accepted. If they still have concerns, you may get a second chance to revise or your paper can be rejected. In short, you try to do your best when you get a chance to revise your work. I have explained this to let you know that I worked on both preparing and revising some papers in September 😊.
This fall, I also welcomed some students to work on some new projects. I am very excited to be able to work with these enthusiastic and motivated minds.
Those are some of the highlights of this season that bring out two important roles I play – a researcher and an educator. If you reflect on this, I am better described by two roles instead of one.
In the world of AI and data-driven research, often more than one source/role/variable/factor is used to describe your problem in terms of data. As human beings, we can visualize three factors (e.g., height, width, depth) with ease. When a fourth factor (e.g., time) comes into play, the visualization gets difficult. This difficulty increases with the increase in the number of factors, often called dimensions.
AI models can handle high-dimensional data with hundreds or thousands of variables and process them at a great speed. These models are getting better at it with advances in algorithms and computing power.
They also generate content, such as images, text, and videos, and are considered creative. This type of AI is called Generative AI. It is evident now that Generative AI will continue to shape our coming days in unique ways.
Let’s see how the future unfolds through responsible use of this technology.
With hopes for a better future,
Best,
Ashirbani
Dr. Ashirbani Saha is the first holder of the BRIGHT Run Breast Cancer Learning Health System Chair, a permanent research position established by the BRIGHT Run in partnership with McMaster University.
