Your product can appeal to more doctors.

We are a weird bunch.

Med school and residency trains us to think in a way that is not intuitive to non-doctors which is why the potential patient/doctor gap exists.

We listened to our attendings, mostly. How can this help you?

I am different from most doctors in the fact you are reading this. I am similar to most radiologists as I read thousands of cat scans, MRIs and ultrasounds each year. I taught residents for years.

I can help you frame your message and craft your interface in a way doctors will respond.

If you are comfortable with your market share, I am not for you.

If you are open to tap new markets and willing to accept doctor’s idiosyncrasies, let’s get your product in their workflow.

Doctors want efficiency. They want utility. They want it to work, right now or have someone fixing it 5 minutes ago.

This is not new.

Tony Hsieh did it with shoes, why is taking so long for EHR’s, PACS and other products and services in our workflow?

Doctors want to understand how it works – a little. We don’t all remember the Krebs cycle, but we understand it.

I can help you breakdown the barriers.

Dr. Vachon has served in many leadership roles during his 16 year career in Navy Medicine.

Each time he has been recognized as THE person to quickly assess his new situation, craft an initial plan and begin. Always taking in data and adjusting course along the way until success.

2016 – 2017 Head, Radiology Department Naval Hospital Okinawa – Complete redesign of the entire department, in Progress

2015-2016 Informatics Division Officer, Naval Medical Center San Diego – US Navy Radiologist of the Year

2013-2014 Radiology Resident, Naval Medical Center San Diego – Junior officer of the quarter

2009-2010 Ace Combat Element Flight Surgeon, VMM 263 – Flight Surgeon of the Year


Leigh and I wrote this book to help radiologists.

With all of the news of artificial intelligence and machine learning it can be daunting to find a place to start.

You will need no computer background to read this book.

Program directors or professors may use this a tool to introduce AI and ML to trainees.

The book will present the difference between artificial intelligence, machine learning and neural networks. You will learn that a neural network is similar to human brains and ‘layers’ are similar to synapses.

Just like the first few years of medical school presented new vocabulary, ML and AI have some particular words that are described simply.

There are some similarities between residency training and ‘training an algorithm’ which will be explained.

After reading this book, you will be prepared to read radiology journal articles that showcase AI and ML applications.

Ty Vachon, MD ML Machine Learning Artificial Intelligence AI Radiology

How can I help?

Let’s discuss the best solution for you and your company.