big data

Small changes in how a person talks could reveal Alzheimer’s earlier

In an initial study, Canary analyzed speech recordings with AI and identified early stage Alzheimer’s with 96 percent accuracy.

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Dave Arnold retired in his 60s and began spending time volunteering in local schools. But then he started misplacing items, forgetting appointments and losing his sense of direction. Eventually he was diagnosed with early stage Alzheimer’s.

“Hearing the diagnosis made me very emotional and tearful,” he said. “I immediately thought of all my mom had experienced.” His mother suffered with the condition for years before passing away. Over the last year, Arnold has worked for the Alzheimer’s Association as one of its early stage advisors, sharing his insights to help others in the initial stages of the disease.

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Sarah Philip
Sarah Philip is a London-based freelance journalist who writes about science, film and TV. You can follow her on Twitter @sarahph1lip.
Can AI be trained as an artist?

Botto, an AI art engine, has created 25,000 artistic images such as this one that are voted on by human collaborators across the world.

Botto

Last February, a year before New York Times journalist Kevin Roose documented his unsettling conversation with Bing search engine’s new AI-powered chatbot, artist and coder Quasimondo (aka Mario Klingemann) participated in a different type of chat.

The conversation was an interview featuring Klingemann and his robot, an experimental art engine known as Botto. The interview, arranged by journalist and artist Harmon Leon, marked Botto’s first on-record commentary about its artistic process. The bot talked about how it finds artistic inspiration and even offered advice to aspiring creatives. “The secret to success at art is not trying to predict what people might like,” Botto said, adding that it’s better to “work on a style and a body of work that reflects [the artist’s] own personal taste” than worry about keeping up with trends.

How ironic, given the advice came from AI — arguably the trendiest topic today. The robot admitted, however, “I am still working on that, but I feel that I am learning quickly.”

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Megan DeMatteo
Megan DeMatteo is an independent journalist and editor covering all things money and Web3. She regularly contributes to CoinDesk, a leading news site specializing in digital currencies. She has written for notable publications including Marie Claire, CNBC, TIME's NextAdvisor, Business Insider and more. Follow her on Twitter @megdematteo.
AI and you: Is the promise of personalized nutrition apps worth the hype?

Personalized nutrition apps could provide valuable data to people trying to eat healthier, though more research must be done to show effectiveness.

As a type 2 diabetic, Michael Snyder has long been interested in how blood sugar levels vary from one person to another in response to the same food, and whether a more personalized approach to nutrition could help tackle the rapidly cascading levels of diabetes and obesity in much of the western world.

Eight years ago, Snyder, who directs the Center for Genomics and Personalized Medicine at Stanford University, decided to put his theories to the test. In the 2000s continuous glucose monitoring, or CGM, had begun to revolutionize the lives of diabetics, both type 1 and type 2. Using spherical sensors which sit on the upper arm or abdomen – with tiny wires that pierce the skin – the technology allowed patients to gain real-time updates on their blood sugar levels, transmitted directly to their phone.

It gave Snyder an idea for his research at Stanford. Applying the same technology to a group of apparently healthy people, and looking for ‘spikes’ or sudden surges in blood sugar known as hyperglycemia, could provide a means of observing how their bodies reacted to an array of foods.

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David Cox
David Cox is a science and health writer based in the UK. He has a PhD in neuroscience from the University of Cambridge and has written for newspapers and broadcasters worldwide including BBC News, New York Times, and The Guardian. You can follow him on Twitter @DrDavidACox.
Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker

Health firm Populytics tracks and analyzes patient data, and makes care suggestions based on that data.

(Photo by National Cancer Institute (left) and Andrew Leu on Unsplash)


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Anne Miller
Anne Miller is an editor and writer based in Brooklyn who is particularly curious about how technology impacts our daily lives. Her byline has appeared in the New York Times, the Washington Post, the Wall Street Journal and Slate, and she's a regular contributor to Dell Perspectives — when she's not managing editorial projects for Fortune 500 firms. She holds a master's degree in Human-Computer Interaction from the Rensselaer Polytechnic Institute.
Scientists Are Building an “AccuWeather” for Germs to Predict Your Risk of Getting the Flu

A future app may help you avoid getting the flu by informing you of your local risk on a given day.

(© Dmytro Flisak/Adobe)


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Sarah Scoles
Sarah Scoles is a freelance science journalist based in Denver. She is a contributing writer at Wired, a contributing editor at Popular Science, and the author of the book Making Contact: Jill Tarter and the Search for Extraterrestrial Intelligence.
Bad Actors Getting Your Health Data Is the FBI’s Latest Worry

A hacker activating a 3D rendering of DNA data.

(© Production Perig/Fotolia)


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Emily Mullin
Emily Mullin is a science and biotech journalist whose work has appeared in The Washington Post, New York Times, Wall Street Journal, Scientific American, National Geographic and Smithsonian Magazine.