May 17, 2020

Google outlines its plans to harness AI in healthcare

Google
artificial intelligence. digital health
Google
Digital health
Catherine Sturman
3 min
artificial intelligence (Getty Images)
Recently rebrandingits Google Research division to Google AI, at Google’s 2018 I/O, festival, the technology giant has revealed its ongoing plans to h...

Recently rebranding its Google Research division to Google AI, at Google’s 2018 I/O, festival, the technology giant has revealed its ongoing plans to harness artificial intelligence and machine learning across a multitude of consumer technologies. However, health technology is gaining traction, and the company continues to grow apace in this space.

Recently partnering with Fitbit, the company will seek to use its cloud healthcare API, founded on Fast Health Interoperability Resources (FHIR) to connect user data with electronic medical records (EMR).

Following on from Fitbit’s recent acquisition of Twine Health (now rebranded as the Fitbit Health Platform), the collaboration will also open doors for the duo to provide solutions to those with chronic, long-term health solutions.

“At Google, our vision is to transform the way health information is organised and made useful,” explained Gregory Moore MD, PhD, Vice President, Healthcare, Google Cloud.

With this in mind, the company has unveiled its new consumer health apps and new smartwatch, all which will successfully integrate with healthcare organisations EMR systems.

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"Artificial intelligence and machine learning are not just technologies of the future. I can assure you that the best artificial intelligence and machine learning in the world is already in your pockets," noted Greg Corrado, Principal Scientist and Director of Augmented Intelligence Research at Google.

In a recent blog, the company has explained how it is working to recognise patterns or “signals” in EMR’s, utilising AI to drive data-driven health outcomes. However, this has remained a complex feat. Working in partnership with a number of healthcare providers, such as UC San Francisco, Stanford Medicine and the University of Chicago, Google has sought to implement deep learning models to make essential predictions regarding patients in hospital through de-identified electronic medical records.

“For each prediction, a deep learning model reads all the data-points from earliest to most recent and then learns which data helps predict the outcome. Since there are thousands of data points involved, we had to develop some new types of deep learning modelling approaches based on recurrent neural networks (RNNs) and feedforward networks. We engineered a computer system to render predictions without hand-crafting a new dataset for each task, in a scalable manner,” Google explained.

Additionally, by utilising the area-under-the-receiver-operator curve to measure the accuracy of its findings, Google has distinguished those with particular traits against those which don’t. However, the company has been keen to stress that such technology is not set to replace medical professionals, but rather enhance the patient experience.

“The model is more like a good listener rather than a master diagnostician,” it adds

 

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Jun 18, 2021

Skin Analytics wins NHSX award for AI skin cancer tool 

AI
NHS
skincancer
Cancer
2 min
Skin Analytics uses AI to detect skin cancer and will be deployed across the NHS to ease patient backlogs

An artificial intelligence-driven tool that identifies skin cancers has received an award from NHSX, the NHS England and Department of Health and Social Care's initiative to bring technology into the UK's national health system. 

NHSX has granted the Artificial Intelligence in Health and Care Award to DERM, an AI solution that can identify 11 types of skin lesion. 

Developed by Skin Analytics, DERM analyses images of skin lesions using algorithms. Within primary care, Skin Analytics will be used as an additional tool to help doctors with their decision making. 

In secondary care, it enables AI telehealth hubs to support dermatologists with triage, directing patients to the right next step. This will help speed up diagnosis, and patients with benign skin lesions can be identified earlier, redirecting them away from dermatology departments that are at full capacity due to the COVID-19 backlog. 

Cancer Research has called the impact of the pandemic on cancer services "devastating", with a 42% drop in the number of people starting cancer treatment after screening. 

DERM is already in use at University Hospitals Birmingham and Mid and South Essex Health & Care Partnership, where it has led to a significant reduction in unnecessary referrals to hospital.

Now NHSX have granted it the Phase 4 AI in Health and Care Award, making DERM available to clinicians across the country. Overall this award makes £140 million available over four years to accelerate the use of artificial intelligence technologies which meet the aims of the NHS Long Term Plan.

Dr Lucy Thomas, Consultant Dermatologist at Chelsea & Westminster Hospital, said: “Skin Analytics’ receipt of this award is great news for the NHS and dermatology departments. It will allow us to gather real-world data to demonstrate the benefits of AI on patient pathways and workforce challenges. 

"Like many services, dermatology has severe backlogs due to the COVID-19 pandemic. This award couldn't have come at a better time to aid recovery and give us more time with the patients most in need of our help.”

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