health & medicine


Transforming Clinical Trials with the Power of AI

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Developing prescription drugs is a high-cost, high-risk endeavor. Average research and development for an approved prescription drug requires an investment of $2.9 billion and takes more than 11 years. Clinical trials alone can cost an average of $1.1 billion over 6.6 years. In fact, clinical trials account for a staggering 40 percent of the pharmaceutical industry's research budget. To make matters worse, only 14 percent of drugs that enter clinical trials are eventually approved.


Where are the opportunities for medtech and pharma in 2020?

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It's that time when we start to look ahead to what next year holds for the life science sector...Lu Rahman outlines 2020s big medtech players A decade ago the healthcare advances create by AI would have seemed the stuff of dreams. But back in 2018 Theresa May announced plans to use artificial intelligence and data to transform the way certain diseases like cancer. The technology is moving at a pace – this year we heard that a team led by the University of Surrey had filed the first ever patent for inventions autonomously created by AI without a human inventor. Professor Ryan Abbott explained the implications this had for the life science sector: "These filings are important to any area of research and development as well as any area that relies on patents. Patents are more important in the life sciences than in many other areas, particularly for drug discovery. These tasks can be the foundation for patent filings. "As AI is becoming increasingly sophisticated, it is likely to play an increasing role in R&D including in the life sciences.


Software Ate The World, Now AI Is Eating Software

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Marc Andreessen famously said that "Software is eating the world" and everyone gushed into the room. This was as much a writing on the wall for many traditional enterprises as it was wonderful news for the software industry. Still no one actually understood what he meant. "Today, the world's largest bookseller, Amazon, is a software company -- its core capability is its amazing software engine for selling virtually everything online, no retail stores necessary. On top of that, while Borders was thrashing in the throes of impending bankruptcy, Amazon rearranged its web site to promote its Kindle digital books over physical books for the first time. Now even the books themselves are software."


US health insurance firm Cigna is using AI to check if patients are taking their medications

Daily Mail - Science & tech

A US health insurance giant is using an AI system to monitor whether patients with chronic diseases are skipping their medication. Cigna's technology, Health Connect 360, will be rolled out to millions of Americans next month. But experts fear the technology will be used to cancel policies or avoid paying up if patients are found to be missing or incorrectly taking prescriptions. Doctors and nurses will be able to constantly keep an eye on patients' health and step in when they have cause for concern. For example, an alert may be triggered if patients forget to pick up their prescription or miss an appointment.


Cigna Uses AI To Check If Patients Are Taking Their Medications - Slashdot

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An anonymous reader quotes a report from The Wall Street Journal: Cigna plans to expand a system that uses artificial intelligence to identify gaps in treatment of chronic diseases, such as patients skipping their medications, and deliver personalized recommendations for specific patients. The product, called Health Connect 360, integrates data from a combination of sources and analytical tools, some developed at Cigna and others brought in as part of its $54 billion acquisition of pharmacy-benefit manager Express Scripts Holding Co., completed late last year. Express Scripts, which began developing the service two years ago, rolled out portions of it to some customers this year. Health Connect 360 was developed for treatment of chronic diseases, including diabetes and heart disease, as well as for pain management. The system aggregates medical, pharmacy, lab and biometric data -- such as information from glucometers, which measure blood-sugar levels -- into a dashboard that is accessible through an online interface.



This AI can detect ADHD better than humans

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A team of researchers used a type of artificial intelligence to predict attention deficit hyperactivity disorder (ADHD) in patients by having it analyze magnetic resonance imaging (MRI) scans. According to a new paper published in the journal Radiology: Artificial Intelligence, their technique could also be used to spot other neurological conditions. Health care professionals have increasingly been relying on MRI scans to understand ADHD, a brain disorder that often causes patients to be restless, and makes it more difficult for them to pay attention. More than eight percent of children in the U.S. have been diagnosed with the condition according to The American Psychiatric Association (APA). Research suggests that a breakdown in the connections between the different regions of the brain, the so-called connectome, causes ADHD.


Exciting use cases of Artificial Intelligence in four industry sectors -

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As the digital transformation of businesses and services continues with full force, artificial intelligence (AI) has become somewhat of a buzzword in the technology sector. While it's true that we haven't quite reached the level of technology sophistication often shown off in Hollywood blockbusters, there already are a variety of use cases where machine learning algorithms are being deployed to improve different aspects of our daily lives. Below, we look at four industries that are reaping the rewards of using AI and what this might mean for the future. Healthcare is one of the most promising areas likely to be transformed significantly by AI and machine learning. This is because this technology can quickly go through large amounts of data and find patterns that humans might miss.


r/artificial - For Neuralink run tests to see if you can put thoughts into someone or something's head

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Easy enough to abstract information from someone's mind, but you'll know you're getting somewhere when you put information "in." Like maybe if you can get a monkey to "get the red ball" and they routinely do after having the thought put in their mind. Or for human trials have then be given a question they could know the answer to if the thought insertion worked. You shouldn't be trying to get a brain and a computer to work directly in tandem. Not at all compatible, but you can translate thoughts into computer code, have the computer do the processing and then insert the thought back.


r/MachineLearning - [R] ProteinNet: a standardized data set for machine learning of protein structure (call for contributions, June 2019)

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I called for "call for contributions" recently, but it didn't end well. People were too obsessed with keeping their secrets and know little outside of ML. So I searched myself for challenging problems in science, with high meaningful impact, potential for ML to make breakthrough, ready dataset and benchmark, and I found this ProteinNet for protein folding. These scientists seem to think for the sake of science as a whole, and want to see how ML can help advance their field. You are welcome to use it for your side project if you are already tired of old time CV or NLP tutorials.