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*Applause* YouTube's caption upgrade shows how machine learning is helping the disabled

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FCC rules require TV stations to provide closed captions that convey speech, sound effects, and audience reactions such as laughter to deaf and hard of hearing viewers. YouTube isn't subject to those rules, but thanks to Google's machine-learning technology, it now offers similar assistance. YouTube has used speech-to-text software to automatically caption speech in videos since 2009 (they are used 15 million times a day). Today it rolled out algorithms that indicate applause, laughter, and music in captions. More sounds could follow, since the underlying software can also identify noises like sighs, barks, and knocks.


Robotics the future of medicine - Business - NZ Herald News

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Computing and robotics is changing the face of medicine at a faster rate than ever before, and is going to affect the way we treat patients says a medical expert. Michael Gillam, who is heading to the SingularityU summit in Christchurch next month, is a physician, medical informatics expert and IT health specialist. He is also one of four directors that built and sold the patient information software Amalga which became one of Microsoft's flagship products. According to Gillam, as computing power continues to increase and the cost of testing and research decreases, health providers will be able to tailor treatment to patients. "When I started studying there were a few known types of blood cancers and by 2005, there were over 80 different types so we've come a long way," Gillam said.


Microsoft's cancer moonshot: Debug the disease as if it's a computer glitch

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Microsoft researchers are doing a bug bash on cancer, complete with software code names like "Project Hanover." Some of them are actually drilling down into our genetic code, looking for ways to reprogram the immune system to combat cancer cells more effectively. "If you can do computing with biological systems, then you can transfer what we've learned in traditional computing into medical or biotechnology applications," Microsoft's Neil Dalchau says in the company's in-depth report about its cancer moonshots. Others are enlisting the power of cloud computing to identify which treatment would work best for a particular cancer patient, based on his or her personalized medical profile. Microsoft and AstraZeneca are already using a software tool known as the Bio Model Analyzer to figure out why leukemia patients respond differently to different treatments.


How Microsoft is helping to 'solve' cancer

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A subset of those scientists, engineers and programmers have a different goal: They're trying to use computer science to solve one of the most complex and deadly challenges humans face: Cancer. And, for the most part, they are doing so with algorithms and computers instead of test tubes and beakers. "We are trying to change the way research is done on a daily basis in biology," said Jasmin Fisher, a biologist by training who works in the programming principles and tools group in Microsoft's Cambridge, U.K., lab. One team of researchers is using machine learning and natural language processing to help the world's leading oncologists figure out the most effective, individualized cancer treatment for their patients, by providing an intuitive way to sort through all the research data available. Another is pairing machine learning with computer vision to give radiologists a more detailed understanding of how their patients' tumors are progressing.


Here's How Artificial Intelligence Could Cure Cancer

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Will we cure cancer using artificial intelligence? Microsoft is one of the growing number of major technology companies betting on it. The company announced Monday the efforts of its various research labs that are using machine learning, artificial intelligence, and other computer science to help doctors research, diagnose, track, and potentially cure various types of cancer. Microsoft is effectively using artificial intelligence to solve a very human problem. One team is helping oncologists use natural language processing to sift through cancer research.


Microsoft wants to 'solve' cancer in the next 10 years using AI

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Microsoft is working towards fighting cancer using computer science such as machine learning and algorithms. By treating cancer like an information processing system, Microsoft researchers are able to adapt tools typically used to model computational processes to model biological ones. Ultimately, the company hopes to create molecular computers to program the body to fight cancer cells immediately after detection. "We are trying to change the way research is done on a daily basis in biology," said Jasmin Fisher, a senior researcher who works in the programming principles and tools group in the Microsoft's research lab in Cambridge. This is combined with a data-driven approach; putting machine learning at the core of Microsoft's attempts to try to tackle the disease.


Australia to play role in IBM cognitive eye health project

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Researchers at IBM Australia will play a role in building a "cognitive assistant" the IT giant hopes will help ophthalmologists diagnose eye conditions from medical image data. "IBM research is building the next generation cognitive assistant with advanced multi-media capability for early detection and management of diseases that can affect both the eyes and overall health of a person," the firm said in a now closed advertisement. Participating full and part-time interns would apply their clinical knowledge to analyse retinal image data and come up with "novel ideas and insights for cognition on this type of data". Back in June, IBM Australia revealed agreements with organisations including Melanoma Institute Australia to "apply cognitive computing to dermatology images" in the hope of earlier detection and identification of skin cancer.



Statisticians step up to aid neurological health research - Faculty of Science - University of Alberta

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Linglong Kong (mathematical and statistical sciences) is the co-lead of a new collaboration of 18 researchers across North America working together to improve the way neuroimaging data is analyzed. In the hands of the right reader, it may prove to be a very important one--such as the likelihood of a particular patient developing a neurological disorder like dementia or responding positively to a new treatment for depression or ADHD. Recent rapid innovations in technology have enabled the unprecedented collection of complex neuroimaging data to measure different perspectives on brain structures and functions. This information-rich data offers incredible potential to investigate neurological and psychiatric diseases, trace neural network changes of various disorders and understand the inner workings of the human brain--helping lay the foundation for a future with more precise, patient-specific medical treatment options. Some of the more complicated problems involve integrating complementary sources of information--such as those that arise from studies that collect data using multiple neuroimaging modalities simultaneously, or studies that aim to combine brain imaging with genomics.


5 ways artificial intelligence is changing the face of healthcare

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Artificial intelligence is advancing rapidly and poised to change the status quo in any number of industries, including healthcare. A recent report by Frost & Sullivan predicts the AI market in healthcare will reach 6 billion by 2021, up from just 600 million two years ago. With the shift to a value-based reimbursement model, ushered in with the Affordable Care Act, hospitals and providers are looking for new ways to increase efficiencies and improve patient outcomes. Cognitive solutions such as IBM's Watson system can assess huge amounts of patient data, provide guidance and decision support, and improve clinical workflow. The goal is to support the physician, not replace him or her, said Anil Jain, vice president of IBM's Watson Health and an internist and medical informatics specialist at the Cleveland Clinic.