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Author: Dr. Vachon

20 Years after Deep Blue: How AI Has Advanced Since Conquering Chess

16Jun By Dr. Vachon

IBM AI expert Murray Campbell reflects on the machine’s long, bumpy road to victory over chess champ Garry Kasparov

Sourced through Scoop.it from: www.scientificamerican.com

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Data science in healthcare comes to medical imaging technology

16Jun By Dr. Vachon

Data science in healthcare merged with advanced medical imaging technology is integral to value-based and personalized care, Philips executive says.

Sourced through Scoop.it from: searchhealthit.techtarget.com

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7 Historic Changes That Have Transformed the Future Of Entrepreneurship

16Jun By Dr. Vachon

Know your paradigm shifts to keep up with the changing world of innovation.

Sourced through Scoop.it from: news.google.com

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Fact or Fallacy: Could Artificial Intelligence Replace Doctors?

16Jun By Dr. Vachon

As medical professionals continue to turn to machine-learning technology like IBM Watson to boost diagnosis and treatment, we address myths and truths about introducing AI for healthcare.

Sourced through Scoop.it from: healthtechmagazine.net

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Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework

14Jun By Dr. Vachon

Article

Sourced through Scoop.it from: www.nature.com

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Artificial Intelligence: A Primer – Garage Technology Ventures

14Jun By Dr. Vachon

Garage Technology Ventures is a seed and early-stage venture capital fund.

Sourced through Scoop.it from: www.garage.com

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Creating Your First Machine Learning Classifier Model in Sklearn

14Jun By Dr. Vachon

Okay, so you’re interested in machine learning. But you don’t know where to start, or perhaps you have read some theory, but don’t know how to implement what…

Sourced through Scoop.it from: www.datasciencecentral.com

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The Optimistic Promise of Artificial Intelligence

14Jun By Dr. Vachon

Andrew Ng and Tong Zhang on how AI is going to be like electricity, transforming every industry.

Sourced through Scoop.it from: www.wsj.com

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Essential Cheat Sheets for Machine Learning and Deep Learning Engineers

14Jun By Dr. Vachon

Learning machine learning and deep learning is difficult for newbies. As well as deep learning libraries are difficult to understand. I am creating a repository on Github(cheatsheets-ai) with cheat…

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Facebook’s Image-Recognition Tech Is Teaching 40,000 Images A Second To Understand Context

13Jun By Dr. Vachon

The company said it was able to train industry standard data sets that used to take days in just an hour.

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A Radiologist’s Introduction to AI and Machine Learning

Summary: A Radiologist’s Introduction to AI and Machine Learning

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.

Available on Amazon

“A Radiologist Introduction to AI and Machine Learning” available on Amazon

Ty Vachon, MD ML Machine Learning Artificial Intelligence AI Radiology
With all of the news of artificial intelligence and machine learning it can be daunting to find a place to start. This short book is for radiologists, radiology residents and medical students who want to learn the basics. 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.
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