therapeutic area


There's a big problem with AI: even its creators can't explain how it works

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Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn't look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn't follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it. Getting a car to drive this way was an impressive feat.


Artificial Intelligence in the Spotlight • MedicalExpo e-Magazine

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Artificial intelligence (AI) was a key topic at both MEDICA and the RSNA conference this year. But what are its applications in healthcare in general and radiology in particular? And what are the barriers? Dr. Michael Forsting, director of the Institute of Diagnostic and Interventional Radiology and Neuroradiology at Essen University Hospital in Germany talked to MedicalExpo e-magazine about his experiences with AI. MedicalExpo e-magazine: What are the major challenges facing AI in healthcare?


AI diagnostics are coming

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Earlier this year, artificial intelligence scientist Sebastian Thrun and colleagues at Stanford University demonstrated that a "deep learning" algorithm was capable of diagnosing potentially cancerous skin lesions as accurately as a board-certified dermatologist. The cancer finding, reported in Nature, was part of a stream of reports this year offering an early glimpse into what could be a new era of "diagnosis by software," in which artificial intelligence aids doctors--or even competes with them. Experts say medical images, like photographs, x-rays, and MRIs, are a nearly perfect match for the strengths of deep-learning software, which has in the past few years led to breakthroughs in recognizing faces and objects in pictures. Companies are already in pursuit. Verily, Alphabet's life sciences arm, joined forces with Nikon last December to develop algorithms to detect causes of blindness in diabetics.


Can Artificial Intelligence Really Identify Suicidal Thoughts? Experts Aren't Convinced

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Australian experts have spoken out about a recent US study that claimed to show artificial intelligence can identify people with suicidal thoughts - by analysing their brain scans. It sounds promising - but it's worth pointing out only 79 people were studied, so are the results enough to show this is a path worth pursing? The research, published in Nature, studied brain activity in subjects when presented with a number of different words - like death, cruelty, trouble, carefree, good and praise. A machine-learning algorithm was then trained to see the nureal response differences between the two groups involved - those with suicidal thoughts, and those with non-suicidal thoughts. And it showed promise - the algorithm correctly identified 15 of 17 patients as belonging to the suicide group, and 16 of 17 healthy individuals as belonging to the control group.


AI-Powered Microscope Counts Malaria Parasites in Blood Samples

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Today, a Chinese manufacturer and a venture backed by Bill Gates will announce plans to commercialize a microscope that uses deep learning algorithms to automatically identify and count malaria parasites in a blood smear within 20 minutes. AI-powered microscopes could speed up diagnosis and standardize detection of malaria at a time when the mosquito-borne disease kills almost half a million people per year. An experimental version of the AI-powered microscope has already shown that it can detect malaria parasites well enough to meet the highest World Health Organization microscopy standard, known as competence level 1. That rating means that it performs on par with well-trained microscopists, although the researchers note that some expert microscopists can still outperform the automated system. That previous research, presented at the International Conference on Computer Vision [pdf] in October, has inspired the Global Good Fund--a partnership between the company Intellectual Ventures and Bill Gates--and a Chinese microscope manufacturer called Motic to take the next big commercialization step.


Artificial Intelligence Is Putting Ultrasound on Your Phone

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If Jonathan Rothberg has a superpower, it's cramming million-dollar, mainframe-sized machines onto single semiconductor circuit boards. The entrepreneurial engineer got famous (and rich) inventing the world's first DNA sequencer on a chip. And he's spent the last eight years sinking that expertise (and sizeable startup capital) into a new venture: making your smartphone screen a window into the human body. Last month, Rothberg's startup Butterfly Network unveiled the iQ, a cheap, handheld ultrasound tool that plugs right into an iPhone's lightning jack. You don't have to be a technician to use one--its machine learning algorithms guide the user to find what they might be looking for.


Everyone wants to run an AI company

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As machine learning and AI become ever more powerful and useful, companies are scrambling to hire chief AI officers and to train their staffs to use the latest AI tools. Andrew Ng, a well-known AI expert, will argue at EmTech MIT in Cambridge, MA, that making use of the technology requires a deeper change. To truly become "AI-first," companies need to understand how AI can creep into their existing products and services and generate entirely new ones. The annual MIT Technology Review event, which kicks off today, will explore how the latest technologies--including AI--are affecting businesses. Ng has a great deal of experience in this area.


Artificial Intelligence Is Putting Ultrasound on Your Phone

#artificialintelligence

If Jonathan Rothberg has a superpower, it's cramming million-dollar, mainframe-sized machines onto single semiconductor circuit boards. The entrepreneurial engineer got famous (and rich) inventing the world's first DNA sequencer on a chip. And he's spent the last eight years sinking that expertise (and sizeable startup capital) into a new venture: making your smartphone screen a window into the human body. Last month, Rothberg's startup Butterfly Network unveiled the iQ, a cheap, handheld ultrasound tool that plugs right into an iPhone's lightning jack. You don't have to be a technician to use one--its machine learning algorithms guide the user to find what they might be looking for.


Eugenics 2.0: We're at the dawn of choosing embryos by health, height, and more

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Nathan Treff was diagnosed with type 1 diabetes at 24. It's a disease that runs in families, but it has complex causes. More than one gene is involved. And the environment plays a role too. So you don't know who will get it.


AI Has Learned to Spot Suicidal Tendencies from Brain Scans

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Suicide is the second-leading cause of death among young people between the ages of 15 and 34 in the United States, and clinicians have limited tools to identify those at risk. A new machine-learning technique documented in a paper published today in Nature Human Behaviour (PDF) could help identify those suffering from suicidal thoughts. Researchers looked at 34 young adults, evenly split between suicidal participants and a control group. Each subject went through a functional magnetic resonance imaging (fMRI) and were presented with three lists of 10 words. All the words were related to suicide (words like "death," "distressed," or "fatal"), positive effects ("carefree," "kindness," "innocence"), or negative effects ("boredom," "evil," "guilty").