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45 digital health startups that raised money in Q3 2016


For the third quarter of 2016, MobiHealthNews tracked just shy of 600 million in deals. While a few large deals anchored the quarter, the majority of the 45 we tracked this quarter were small; only seven were more than 20 million, most were 10 million or less. For this analysis, we've omitted investments in joint ventures like Verily and Sanofi's OnDuo as well as grant funding. Read on for the 45 deals in the digital health space we tracked throughout the quarter, listed in order from largest to smallest amount of funding. Canada-based wearable technology company Thalmic Labs, which makes the connected armband Myo, raised 120 million in Series B funding in a round led by Intel Capital, the Amazon Alexa Fund and Fidelity Investments Canada.

Meet the Food Technology That May Save the Planet: Plant-Based Protein


As the world's human population continues to grow, the question of how we're going to meet the protein needs of the planet is rapidly becoming the biggest challenge of our time. It's no secret that the developed world is obsessed with protein, with the average person in the U.S. consuming 103 grams per day, around double the actual recommended amount, two-thirds of which comes from animal sources. On the other hand, animal protein consumption is on the rise in developing countries like China and India because of rising incomes and improved quality of life. Forecasts suggest that in a few decades, developing countries' consumption of animal protein will reach the current levels of the developed world. But what most people don't realize is the tremendous cost producing animal protein has on the planet.

Millions of veteran health care records are being used to train this startup's artificial intelligence


Last spring the startup Flow Health began a five-year contract with the Department of Veteran Affairs to examine all historic and ongoing medical records. The startup will use information obtained from those records to train artificial intelligence to, among other things, fight illness and predict disease for the more than eight million people cared for by the Department of Veteran Affairs. Advice and predictions from Flow Health will be presented to health care professionals through Vista, the DoD's open source system for electronic medical records. Doctors can then choose to apply or ignore the advice drawn from the VA's vast storage of medical records. "When a veteran comes in and presents certain clinical symptoms, we can better understand and make predictions about'What is the likely diagnosis?

Equity crowdfunding platform OurCrowd launches an early stage digital health fund


Israel-based equity crowdfunding platform OurCrowd is launching a sector specific fund fully focused on digital health -- touting it as Israel's first fund with such a focus. The fund, called OurCrowd Qure, will invest in early stage startups at the seed and Series A level. Fundraising is starting now, with a target of $50 million for the first raise. Managing partner Dr Yossi Bahagon tells TechCrunch the team expects to make about 15 investments with the first fund. He says typical investments will start at $500,000 for the earliest stage startups, rising to up to about $3 million at the Series A level.

The opportunities and challenges of AI in health care VentureBeat AI


When we asked dozens of venture capitalists where they see the most potential for applied artificial intelligence, they unanimously agreed on health care. Technology has already been used to incrementally improve patient medical records, care delivery, diagnostic accuracy, and drug development, but with AI we could achieve exponential breakthroughs. Deep learning first caught the media's attention when a team from the lab of Geoffrey Hinton at the University of Toronto won a Merck drug discovery competition despite having no experience with molecular biology and pharmaceutical development. Recently, a multidisciplinary research team at Stanford's School of Medicine comprised of pathologists, biomedical engineers, geneticists, and computer scientists developed deep learning algorithms that diagnose lung cancer more accurately than human pathologists. The ultimate dream in health care is to eradicate disease entirely.