Miscellaneous

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Article "Cancer drug development time halved thanks to artificial intelligence"
Artificial intelligence has halved the time it has taken to bring a cancer combatting drug to market, start-up claims

by Ian Douglas
October 9, 2015

 

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Article "Watch Robots Transform A California Hospital"

by Quoctrung Bui
May 27, 2015

 

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Article "Artificial Intelligence Offers a Better Way to Diagnose Malaria"
An algorithm for spotting malaria under the microscope could bring accurate, rapid diagnosis to understaffed areas.

by Anna Nowogrodzki
February 10, 2016

 

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"From Virtual Nurses To Drug Discovery: 90+ Artificial Intelligence Startups In Healthcare"

August 31, 2016

 

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Article "Google Strikes Deal With NHS That Gives AI Unit Access To 1.6 Million Patient Records"

by Catherine Cabral-Isabedra
May 1, 2016

 

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Article "Google handed patients' files without permission: Up to 1.6 million records - including names and medical history - passed on in NHS deal with web giant"
Google agrees new data share deal with Royal Free NHS Trust in London
Internet giant is developing new app to help care for kidney patients
But Google can access complete medical records - not just kidney data
Campaigners unhappy Google will have free access to all patient records

by Sophie Borland and Martin Robinson
May 3, 2016

Google Inc.

 

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Article "The (robot) doctor will see you now – Expert reaction"

May 6, 2016

 

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Article "The next major advance in medicine will be the use of AI"

by Jessica Hall
May 20, 2016

 

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Article "AI can excel at medical diagnosis, but the harder task is to win hearts and minds first"

by Owen A Johnson
August 12, 2016

 

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Article "Startups Disrupting Healthcare with AI and Machine Learning"

September 2, 2016

 

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AT&T Foundry & The Future of Connected Healthcare

Published on Sep 7, 2016

AT&T Foundry is helping physicians and hospitals connect with patients more easily and efficiently through connected devices and state-of-the-art networks. Learn more about Connected Healthcare and the Internet of Things (IoT).

 

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Article "Artificial Intelligence Reads Mammograms With 99% Accuracy"

by Cecille De Jesus
September 25, 2016

 

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Article "Live Saving Medical Devices Could Soon Be Delivered By Drone to Heart Attack Victims"

by Eleazer Corpuz
November 20, 2016

 

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Article "The rise of China’s medical robotics sector"

by Siao Tin Soh
December 22, 2016

 

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Anthony Chang | Data and Machine Learning | Exponential Medicine 2016

Published on Jan 2, 2017

WATCH NOW: Anthony Chang delivers his presentation on Big Data and Machine learning on the first day of Exponential Medicine 2016.

 

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Your robot doctor will see you now

Published on Feb 24, 2017

What happens when you have a medical question that stumps your doctor? How about asking an artificially intelligent medical computer? We look at how AI is poised to transform the way we practice medicine.

 

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Project Abbie

Published on Mar 17, 2017

Project Abbie is inspired by the story of Abbie Benford, who succumbed to complications related to anaphylaxis just eight days before her 16th birthday. The Wyss Institute, in collaboration with Boston Children’s Hospital, is developing a wearable, non-invasive device that could sense anaphylaxis and automatically inject epinephrine in individuals who are unable to do so themselves; a device that could have saved Abbie’s life.

 

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Article "Sports-concussion dilemma: Robot doctors could be the answer in rural America"

by UT Southwestern
April 7, 2017

 

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The robot will see you now – AI and your health care

Published on Apr 25, 2017

Artificial intelligence is now detecting cancer and robots are doing nursing tasks. But are there risks to handing over elements of our health to machines, no matter how sophisticated?

 

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Better Medicine Through Machine Learning | Suchi Saria | TEDxBoston

Published on Oct 12, 2016

Faster medical treatment saves lives. Machine Learning is already saving lives, by scouring a multitude of patients’ data and comparing them to one patient’s health data to detect symptoms 12 to 24 hours sooner than a doctor could. "In many pressing medical problems, the answers to knowing whom to treat, when to treat, and what to treat with, might already be in your data" says Suchi Saria. Learn how TREWS (Targeted Real-time Early Warning Score) is leading the way to save lives.

Suchi Saria is a professor of computer science and health policy, and director of the Machine Learning and Health Lab at Johns Hopkins University. Her research is focused on designing data solutions for providing individualized care.