ABAIM Course Review & Testimonial

This article would be a testimonial to the review course - Artificial Intelligence in Medicine offered by American Board of Artificial Intelligence and Medicine.

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This article would be a testimonial to the review course - Artificial Intelligence in Medicine offered by American Board of Artificial Intelligence and Medicine.

Overview:

For the simple ones who really want to know, on the fence, if they want to attend this course, this is fantastic! For those who want some more details, I'll just go ahead and share more.
Number one, and the most important thing about this course is its comprehensiveness. There are people like me, who have done some clinical decision support work, some computer vision work, but this putting all these pieces that artificial intelligence covers into under one course is just breathtakingly fantastic! And the way it was presented was really good. This is not an intermediate or even advanced level, it is even designed for a beginner introductory level. But to cover all of that under 16 hours within the two day timeframe period was just very good.

Faculty:

The faculty is amazing and the playfulness, the banter, the way they support each other was also very good to see. Because they are very humble and they actually project that as well.
Dr. Anthony presented about the evolution of artificial intelligence, its history, and then went into data science and artificial intelligence in the current era, and gave some basic working knowledge of things.
Then he passed it on to Dr. Alfonzo, who actually took it to the next level by discussing all the different models of artificial intelligence, how they function, what are random forces, what are support vector machines, etc. When you do details about it, it's applicable to medicine as well and giving examples on the way.
While they were doing that, Dr. Bob was actually grateful, and gave meaningful insights about practical data related artificial intelligence questions. Similarly, Dr. Mary was actually fantastic. She's from Georgia Tech Institute, and teaches masters in data sciences, she did a phenomenal job and interjecting wisdom wherever it needs to be.
The two different tangents I suppose, were one with Dr. Arlene Myers, who wrote the book on digital health entrepreneurship. He’s very prolific and did a very good interactive session to actually make sure that we also understand not just the artificial intelligence in healthcare, the core topics from an academic perspective, but actually have a pathway to go to market to have a thinking of entrepreneurs, and how to make these things applicable in a market level.
Dr. Sarah did a fantastic talk on ethics in AI. I would say that she'd won the lottery because everyone's so interested in ethics. Her last two papers are a must read for anyone who is actually interested in ethics and AI.
Other faculty members, especially Dr. Boyko also presented in between, very beautiful small nuggets of wisdom through his practical work in artificial intelligence.
And one last person, Dr. Mijanou, was the best course director that I’ve ever seen. I think this was the smoothest course and she handled it very smoothly and without any hiccups.

Most Valuable Lessons:

The most valuable lessons from this course were that learning is an evolving field in general, but artificial intelligence, such an evolving field, that you have to be vigilant, continuously learn, and be patient. I learned some more humidity from the faculty because being at their level, they were very open to admit that this is an evolving field and is something that we really need to look at into the future.
Another thing is that, “Everyone wants to do the model work, not the data work.” Recently there was an article published on this topic from Google research and there's a YouTube video (1) that I linked below that covers this topic. Again, it is very important to consider the velocity, the variety and the quality of data, because the better that is, your models will be more accurate. And once your models are accurate, they can be generalized and not overfitting to the particular situation you have trained them. So it's great to see that, and then of course, AI is a team sport. So you're working with data scientists, modeling experts, clinicians, subject matter expertise, if you're doing it in radiology, then imaging engineers, etc. So, these are some of the lessons that I think are important for life in general, but are very important for artificial health, artificial intelligence, and healthcare as an evolving field.

Pricing:

The price is fantastic. I bought the package for $600. It included 16 hours of CME as well as certification. Even if you're not intending to get the certification, you should take the course. Because, you may know artificial intelligence, even at an intermediate level. But the question really, is to put that all together into one comprehensive two-day, valuable presentations, which was really amazing! So, it’s way worth the money.

Beneficiaries:

Is this only for physicians? No, about 60% of them are physicians, but there's a reasonable amount of people who are non physician. So that's where the community cohort perspective comes in.

My Feedback:

I gave some feedback but Dr. Anthony told me that he's already working on an intermediate course to include these two important feedbacks:
  1. A workshop that goes through a Data science project all the way to modeling. As a matter of fact, Dr. Hoyt, Bob already conducts an MI society every first Saturday of the month, data science project. And he goes through the process of how to clean data and prepare it for modeling, etc. So that whole workshop is going to be planned for future courses.
  1. The second workshop I requested is to critically appraise a published article. The issue is that there are so many models, and then there are so many flat flavors in the model. So everyone has recipes, and then they change their own recipes according to their will. So artificial intelligence in evolving fields have to critically appraise an article and to understand its true limitations. So to critically appraise an article is extremely important, because these are going to be applied for your patients and it's your job as a physician to make sure that whatever technologies are also applied towards your patient, you are understanding them and applying them appropriately. Because these are all tools.
Other than that, I think the community aspect could be a little better, I suppose there should be a LinkedIn or Telegram group with all the cohorts involved from cohort one to court four, where like minded people gather together and look at different projects and share project updates, resources, etc. That would even reduce work replication.
These are the three books that are must read.
  1. Intelligence-Based Medicine by Anthony C Chang
  1. Introduction to Biomedical Data Science by Robert Hoyt and Robert Muenchen
  1. Digital Health Entrepreneurship by Sharon Wulfovich and Arlen Meyers
Again, I'm very grateful for the course being offered and I would suggest anyone and everyone to take part in this course. Thank you so much!
“If you save a life, it is as if you save the life of all mankind.”

Reference:

  1. https://www.youtube.com/watch?v=Odz8aE1th0M

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