There’s a gold rush going on in the world of health data mining and, unsurprisingly, the established major companies are leading the way. The last article I wrote covered the development and advance of IBM Watson but there’s some serious competition from both Google in the form of DeepMind Health and in the Amazon stealth unit; Amazon 1492.
DeepMind was founded as an independent company in 2010. It cut its teeth through development of an AI learning platform, teaching it how to play old games from the seventies and eighties, which are relatively primitive compared to the ones that are available today.
Google acquired DeepMind in 2014 for $500 million, with a view to exploiting its AI capabilities, particularly in relation to healthcare.
DeepMind developed a programme called AlphaGo that defeated a Go world champion, and arguably the strongest Go player in history. The purpose of this feat was that although Go is a rule-based board game it is also enormously complex; there are 10 to the power of 170 possible board combinations. Given this level of complexity, Go is played primarily through intuition and feel making it the perfect platform to test out the self-learning algorithms.
Training consisted of the introduction of the 100 000 amateur games available on the internet to AlphaGo, after which it acquired the capabilities of a moderate player. AlphaGo then honed its skills by playing itself 30 million times, using “reinforcement learning” to improve to the point where it defeated the world champion. In 2017, an improved version, AlphaGo Zero, defeated AlphaGo 100 games to 0.
DeepMind now has a collaboration with Moorfields Eye Hospital to analyse anonymised eye scans, searching for early signs of diseases leading to blindness.
In August 2016, a research programme with University College London Hospital was announced with the aim of developing an algorithm that can automatically differentiate between healthy and cancerous tissues in head and neck areas.
In November 2017, DeepMind announced a research partnership with the Cancer Research UK Centre at Imperial College London with the goal of improving breast cancer detection by applying machine learning to mammography.
However, it hasn’t all been plain sailing. DeepMind developed an app called Streams, which sends alerts to doctors about patients at risk of acute risk injury. On 13 November 2018, DeepMind announced that its health division and the Streams app would be absorbed into Google Health. Privacy advocates said the announcement betrayed patient trust and appeared to contradict previous statements by DeepMind that patient data would not be connected to Google accounts or services.
There have also been concerns over the agreement between DeepMind and the Royal Free London NHS Foundation Trust. The latter operates three London hospitals where an estimated 1.6 million patients are treated annually. The agreement shows DeepMind Health had access to admissions, discharge and transfer data, accident and emergency, pathology and radiology, and critical care at these hospitals. This included personal details such as whether patients had been diagnosed with HIV, suffered from depression or had ever undergone an abortion in order to conduct research to seek better outcomes in various health conditions.
Subsequent to these problems DeepMind has expanded its focus to include AI ethics, the goal being to fund external research of the following themes: privacy transparency and fairness; economic impacts; governance and accountability; managing AI risk; AI morality and values; and how AI can address the world's challenges. As a result, the team hopes to further understand the ethical implications of AI and aid society in seeing that AI can be beneficial.
Amazon set up 1492, a secret lab dedicated to healthcare innovation in July 2017. Since then, they’ve hired a number of healthcare experts, including the former chief health informatics officer for the U.S. Food and Drug Administration (FDA).
Although information is somewhat scarce 1492 will focus on opportunities in digital healthcare, like Electronic Medical Records and telemedicine.
Headquartered in Seattle, team 1492 is focused on both hardware and software, its aims are:
To extract and use data from Electronic Medical Records system and improve the algorithm to make it more efficient and useful.
To make the data available to the patients and doctors.
To build a platform for telemedicine so that patients can interact virtually with the physicians and specialists regarding their problems.
Exploring various medical applications of hardware like Echo and Dash Wand.
Developing skills for Amazon’s Alexa that can be used for healthcare as well.
Possibly develop medical devices.
In November 2018, Amazon announced its intention to sell a service, hosted on AWS, that uses machine learning to read medical records. This service will be released under the banner of Amazon Comprehend Medical (ACM).
ACM is a HIPAA-eligible machine learning service that allows developers to process unstructured medical text and identify information such as patient diagnosis, treatments, dosages, symptoms and signs, and more. This is a first step to augmenting doctors with AI, but, as with other health AI solutions leads to a minefield of trust and data protection issues. Amazon, with its unique relationship to Prime customers (and others) may be in a uniquely trusted position to overcome these issues.
So, who’s going to be the winner? Given the scale and resources of these companies, probably all of them, but without a doubt the biggest winner of all will be the patient due to the step change advancement in healthcare that these technologies can deliver.
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