How Close Are We To AI-Automated Healthcare? - HIT Consultant

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Editor's Note: Alex Meshkin is the CEO of Flow Health. Flow Health provides longitudinal care plan coordination and chronic care management services built on top of its platform, which is The Operating System for Value-Based CareSM. We have seen incredible progress in machine learning and artificial intelligence (AI) over the past few years, especially through the application of deep learning algorithms. AI systems will get even better as more data is collected, so faster data gathering and better data integration should lead to smarter and more useful AI systems. Recently I described a new class of system that I believe will take form and leverage AI and combine workflow automation to improve how care is delivered -- I termed this: "Intelligent Clinical Decision Automation."


Machine Learning vs Machine Reasoning: Know the Difference

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Since ancient times, humans have been interested in finding systematic approaches to reasoning and logical thinking. Now, we want to make machines "think" like us and endow them with the reasoning ability that, unfortunately, we don't quite understand ourselves. But, why do we need machines that can deconstruct truths and validate reasons like we do? One of our most recent AI-related posts discusses the story of an AI system that can detect skin cancer more accurately than dermatologists. No doubt, this is big a deal in that an early diagnosis is one of the most effective methods for providing successful cancer treatments.


Why AlphaGo Zero is a Quantum Leap Forward in Deep Learning

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The 1983 movie "War Games" has a memorable climax where the supercomputer known as WOPR (War Operation Plan Response) is asked to train on itself to discover the concept of an un-winnable game. The character played by Mathew Broderick asks "Is there any way that it can play itself?" The solution is the same, set the number of players to zero (i.e. There is plenty to digest about this latest breakthrough in Deep Learning technology. DeepMind authors use the term "self-play reinforcement learning". As I remarked in the piece about "Tribes of AI", DeepMind is particularly fond of their Reinforcement Learning (RL) approach. DeepMind has taken the use of Deep Learning layers in combination with more classical RL approaches to an art form.


Why AlphaGo Zero is a Quantum Leap Forward in Deep Learning

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The 1983 movie "War Games" has a memorable climax where the supercomputer known as WOPR (War Operation Plan Response) is asked to train on itself to discover the concept of an un-winnable game. The character played by Mathew Broderick asks "Is there any way that it can play itself?"


Why AlphaGo Zero is a Quantum Leap Forward in Deep Learning

@machinelearnbot

The 1983 movie "War Games" has a memorable climax where the supercomputer known as WOPR (War Operation Plan Response) is asked to train on itself to discover the concept of an un-winnable game. The character played by Mathew Broderick asks "Is there any way that it can play itself?" The solution is the same, set the number of players to zero (i.e. There is plenty to digest about this latest breakthrough in Deep Learning technology. DeepMind authors use the term "self-play reinforcement learning".