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An AI startup tries to take better pictures of the heart

Caption Health provided me with unpublished data from a study in which 8 nurses with no previous experience in cardiac ultrasound performed four different types of scans on 240 patients. For assessing patients’ left ventricular size and function, as well as assessment of pericardial effusion, or fluid around the heart, the AI took the same number of usable images. For each, 240 scans were performed, and 237, or 98.8%, were of sufficient quality, according to a panel of five cardiologists. For images of the right ventricle, which is harder to see, the results were a bit worse: 222 images, or 92.5% of them, were of adequate quality. Eric Topol, the director and founder of the Scripps Research Translational Institute, commented that this was still a small number of samples for AI work; Caption Health said it “respectfully disagrees” because the study was prospective. The goal of the study was to show the test was 80% accurate.

Artificial intelligence needs patients' voice to remake health care - STAT

Health care AI companies currently harness data from electronic health records (EHRs) to build their products. EHRs are incomplete at best, dangerous at worst. They are so saturated with answers to questions required by insurance companies’ reimbursement rules and core measures from the Centers for Medicare and Medicaid Services that they end up having little to do with actual patient care.

First systematic review and meta-analysis suggests artificial intelligence may be as effective as health professionals at diagnosing disease -- ScienceDaily

"We reviewed over 20,500 articles, but less than 1% of these were sufficiently robust in their design and reporting that independent reviewers had high confidence in their claims. What's more, only 25 studies validated the AI models externally (using medical images from a different population), and just 14 studies actually compared the performance of AI and health professionals using the same test sample," explains Professor Alastair Denniston from University Hospitals Birmingham NHS Foundation Trust, UK, who led the research.  "Within those handful of high-quality studies, we found that deep learning could indeed detect diseases ranging from cancers to eye diseases as accurately as health professionals. But it's important to note that AI did not substantially out-perform human diagnosis."

Estonia is using its citizens’ genes to predict disease

“The genetic risk score will be just another tool for doctors. In addition to measuring cholesterol levels, blood pressure, and body mass index, the genetic risk score will be yet another measurement that our prediction algorithm can use,” says Milani. She explains that they’ve already piloted a number of diseases to be diagnosed  by the algorithm, but this currently takes place at the biobank, not in the doctor’s office. “For the genetic information to be used in everyday practice we need to undertake pretty extensive IT developments — which we’re actually starting now. We’re launching the development of automated decision support software for physicians. So when doctors enter various patient data — such as cholesterol level, blood pressure, and smoking status — in the system, then the genetic risk will be calculated by the algorithm, and it’ll provide specific guidance accordingly.” She adds that the final product will be owned by the government, or to be more specific, by the citizens of Estonia.

AI technique detects heart failure from a single heartbeat with 100% accuracy - ScienceBlog.com

Dr Massaro said: “We trained and tested the CNN model on large publicly available ECG datasets featuring subjects with CHF as well as healthy, non-arrhythmic hearts. Our model delivered 100% accuracy: by checking just one heartbeat we are able detect whether or not a person has heart failure. Our model is also one of the first known to be able to identify the ECG’ s morphological features specifically associated to the severity of the condition.”

The Hidden Costs of Automated Thinking | The New Yorker

A world of knowledge without understanding becomes a world without discernible cause and effect, in which we grow dependent on our digital concierges to tell us what to do and when.

The Hidden Costs of Automated Thinking | The New Yorker

There’s far less prestige associated with conceptual papers or papers that provide some new analytical insight,” he said, in an interview. As machines make discovery faster, people may come to see theoreticians as extraneous, superfluous, and hopelessly behind the times. Knowledge about a particular area will be less treasured than expertise in the creation of machine-learning models that produce answers on that subject.

The Hidden Costs of Automated Thinking | The New Yorker

Taken in isolation, oracular answers can generate consistently helpful results. But these systems won’t stay in isolation: as A.I.s gather and ingest the world’s data, they’ll produce data of their own—much of which will be taken up by still other systems. Just as drugs with unknown mechanisms of action sometimes interact, so, too, will debt-laden algorithms.

The Hidden Costs of Automated Thinking | The New Yorker

Theory-free advances in pharmaceuticals show us that, in some cases, intellectual debt can be indispensable. Millions of lives have been saved on the basis of interventions that we fundamentally do not understand, and we are the better for it. Few would refuse to take a life-saving drug—or, for that matter, aspirin—simply because no one knows how it works. But the accrual of intellectual debt has downsides. As drugs with unknown mechanisms of action proliferate, the number of tests required to uncover untoward interactions must scale exponentially. (If the principles by which the drugs worked were understood, bad interactions could be predicted in advance.) In practice, therefore, interactions are discovered after new drugs are on the market, contributing to a cycle in which drugs are introduced, then abandoned, with class-action lawsuits in between. In each individual case, accruing the intellectual debt associated with a new drug may be a reasonable idea. But intellectual debts don’t exist in isolation. Answers without theory, found and deployed in different areas, can complicate one another in unpredictable ways.

Unsupervised word embeddings capture latent knowledge from materials science literature | Nature

Furthermore, we demonstrate that an unsupervised method can recommend materials for functional applications several years before their discovery. This suggests that latent knowledge regarding future discoveries is to a large extent embedded in past publications. Our findings highlight the possibility of extracting knowledge and relationships from the massive body of scientific literature in a collective manner, and point towards a generalized approach to the mining of scientific literature.

Four Rules To Guide Expectations Of Artificial Intelligence

"Our unstated contract with the universe has been if we work hard enough and think clearly enough, the universe will yield its secrets, for the universe is knowable, and thus at least somewhat pliable to our will," Weinberger writes in Everyday Chaos: Technology, Complexity, and How We're Thriving in a New World of Possibility. "But now that our tools, especially machine learning and the internet, are bringing home to us the immensity of the data and information around us, we're beginning to accept that the true complexity of the world far outstrips the laws and models we devise to explain it."

Semiconductor Engineering .:. Spreading Intelligence From The Cloud To The Edge

To handle all of these bits, at least some processing has to be done at the edge. It takes far too much time, energy and money to move it all—and the bulk of it is useless. But so far there is no agreement on how or where this will be done, or by whom. Cloud providers still believe hyperscale data centers are the most efficient tool to grind down the mountains of operational data produced by IoT devices every day. Device makers, in contrast, believe they can pre-process much of that data at or close to the source if they can put a smart enough, purpose-built machine learning inference accelerator in the device.

This Is How You Kill a Profession - The Chronicle of Higher Education

We discarded college faculty in the same way that we discarded medical general practitioners: through providing insane rewards to specialists and leaving most care in the hands of paraprofessionals. We discarded college faculty in the same way that we discarded cab drivers: by leveling the profession and allowing anyone to participate, as long as they had a minimum credential and didn’t need much money. We discarded college faculty in the same way that we discarded magazine and newspaper writers: by relabeling the work “content” and its workers “content providers.” We discarded college faculty in the same way that we discarded local auto mechanics: by making all of the systems and regulations so sophisticated that they now require an army of technicians and specialized equipment. We discarded college faculty in the same way that we discarded bookkeepers: by finally letting women do it after decades of declaring that impossible, and then immediately reducing the status of the work once it became evident that women could, in fact, do it well.

Inflammation links heart disease and depression -- ScienceDaily

This finding was given further support by the next stage of the team's research. They used a technique known as Mendelian randomisation to investigate 15 biomarkers -- biological 'red flags' -- associated with increased risk of coronary heart disease. Mendelian randomisation is a statistical technique that allows researchers to rule out the influence of factors that otherwise confuse, or confound, a study, such as social status. Of these common biomarkers, they found that triglycerides (a type of fat found in the blood) and the inflammation-related proteins IL-6 and CRP were also risk factors for depression. Both IL-6 and CRP are inflammatory markers that are produced in response to damaging stimuli, such as infection, stress or smoking. Studies by Dr Khandaker and others have previously shown that people with elevated levels of IL-6 and CRP in the blood are more prone to develop depression, and that levels of these biomarkers are high in some patients during acute depressive episode. Elevated markers of inflammation are also seen in people with treatment resistant depression. This has raised the prospect that anti-inflammatory drugs might be used to treat some patients with depression. Dr Khandaker is currently involved in a clinical trial to test tocilizumab, an anti-inflammatory drug used for the treatment of rheumatoid arthritis that inhibits IL-6, to see if reducing inflammation leads to improvement in mood and cognitive function in patients with depression. While the link between triglycerides and coronary heart disease is well documented, it is not clear why they, too, should contribute to depression. The link is unlikely to be related by obesity, for example, as this study has found no evidence for a causal link between body mass index (BMI) and depression.

Data Mining Reveals the Six Basic Emotional Arcs of Storytelling - MIT Technology Review

The idea behind sentiment analysis is that words have a positive or negative emotional impact. So words can be a measure of the emotional valence of the text and how it changes from moment to moment. So measuring the shape of the story arc is simply a question of assessing the emotional polarity of a story at each instant and how it changes. Reagan and co do this by analyzing the emotional polarity of “word windows” and sliding these windows through the text to build up a picture of how the emotional valence changes. They performed this task on over 1,700 English works of fiction that had each been downloaded from the Project Gutenberg website more than 150 times.

Machine learning could eliminate unnecessary treatments for children with arthritis: An algorithm predicted disease outcome in children suffering from arthritis, helping doctors better tailor treatment -- ScienceDaily

"We had to use machine learning just to detect these seven patterns of disease in the first place," says Morris, whose team modified the technique known as multilayer non-negative matrix factorization. "And then we realized there are some children who do not fall into any of the patterns and they have a very bad version of the disease. Now we understand the disease much better we can group children into these different categories to predict response to treatment, how fast do they go into remission and whether or not we can tell they are in remission and remove therapy."

Listeners get an idea of the personality of the speaker through his voice -- ScienceDaily

Ratings of perceived personality were highly consistent among listeners regardless of the language in which voices were evaluated. That is, listeners agree in their judgments of whether a given voice sounds aggressive or confident. This suggests that there must be certain invariant properties of the voice that indicate how trustworthy or competent a person is. This is in line with the idea that we can train ourselves to sound more or less competent, more or less dominant, depending on the context (e.g., job interviews). After hearing just one word, listeners rapidly create a social voice space, where voices are grouped according to two main dimensions, one emphasizing traits of valence (trustworthiness, warmth) and other emphasizing strength (dominance, aggressiveness). These two personality dimensions are very relevant and respond to evolutionary pressures. Obtaining information about the intent of the others helps individuals to appropriately evaluate whether to approach or to avoid interaction with others.

Ping An Good Doctor blazes trail in developing unstaffed, AI-assisted clinics in China | South China Morning Post

Each clinic, which is about the size of a traditional telephone booth, enables users to consult a virtual “AI doctor” that collects health-related data through text and voice interactions. After the AI consultation, the information gathered is reviewed by a human doctor who then provides the relevant diagnosis and prescription online. Customers can buy their medicine from the smart drug-vending machine inside the clinic.

Could robots be counselors? Early research shows positive user experience: New research has shown for the first time that a social robot can deliver a 'helpful' and 'enjoyable' motivational interview -- ScienceDaily

"We were pleasantly surprised by how easily the participants adapted to the unusual experience of discussing their lifestyle with a robot," she said. "As we have shown for the first time that a motivational interview delivered by a social robot can elicit out-loud discussion from participants. "In addition, the participants perceived the interaction as enjoyable, interesting and helpful. Participants found it especially useful to hear themselves talking about their behaviour aloud, and liked the fact that the robot didn't interrupt, which suggests that this new intervention has a potential advantage over other technology-delivered adaptations of MI.

New tools create new worlds

Of all the tools we’ve created to augment our intelligence, writing may be the most important. But when he “de-augmented” the pencil, by tying a brick to it, it became much, much harder to even write a single word. And when you make it hard to do the low-level parts of writing, it becomes near impossible to do the higher-level parts of writing: organizing your thoughts, exploring new ideas and expressions, cutting it all down to what’s essential. That was Doug’s message: a tool doesn’t “just” make something easier — it allows for new, previously-impossible ways of thinking, of living, of being.

How To Become A Centaur

But won’t AI eventually get better at the dimensions of intelligence we excel at? Maybe. However, consider the “No Free Lunch” theorem, which comes from the field of machine learning itself.4 The theorem states that no problem-solving algorithm (or “intelligence”) can out-do random chance on all possible problems: instead, an intelligence has to specialize. A squirrel intelligence specializes in being a squirrel. A human intelligence specializes in being a human. And if you’ve ever had the displeasure of trying to figure out how to keep squirrels out of your bird feeders, you know that even squirrels can outsmart humans on some dimensions of intelligence. This may be a hopeful sign: even humans will continue to outsmart computers on some dimensions.

Is This the End of Couple's Therapy?

Incredibly, one in four couples cite temperature control as a primary source of arguments, with 42 percent of men admitting to having turned down the temperature without consulting their partner. “By the time we reach our late 20s, we’ve already figured out for the most part who we are and what we are or are not willing to put up with, which in turn makes it harder to adjust to others’ likes and dislikes and preferences," says Vijayeta Sinh, a New York City-based clinical psychologist. That’s why the best home technologies are the ones that do the compromising for you. “The value of a connected home is you have the simple convenience of, ‘Hey, I don't want to be thinking about how I'm taking care of my building. I want my building to take better care of me,’” says Ben Bixby, general manager of energy and safety at Nest, which recently launched the Nest Thermostat E, an affordable and easy-to-use smart thermostat, which requires zero programming, thanks to its “simple schedule,” blends into the background of your home, and can pay for itself—and then some—with energy savings.* Adds Bixby, “You're not an expert in knowing what temperature it should be when—let the thermostat figure that out!”

FitBit's new sleep tracker is pretty darn cool

imagine what we’ll learn as warehouses worth of enhanced sleep data like get integrated into drug trials, therapy, physical exams, coaching, research and even education.

Google's Improbable Deal to Recreate the Real World in VR | WIRED

Improbable offers a new way of building virtual worlds, including not just immersive games à la Second Life or World of Warcraft, but also vast digital simulations of real cities, economies, and biological systems. The idea is that these virtual worlds can run in a holistic way across a practically infinite network of computers, so that they can expand to unprecedented sizes and reach new levels of complexity.

Vélemény: Gyáva - NOL.hu

During Tickets and all other activities of terrorist attacks in the bus terminal - topped with the words TEK up Janos Hajdu-chief presented to the Prime Minister late-night spectacle . The counterterrorism megfogalmazásunkat probably indignantly rejected, as was a serious exercise. But the commando techniques rarely is often presented to the public and foreign visitors. Sharp right position for the enemy unexpected, but well-rehearsed devices are the most important advantages. This only endangers the public initiation.

Google and Facebook go after Go

Google DeepMind employs more than 200 AI researchers and engineers. Over the 18 months or so it's spent on AlphaGo, the team ballooned from two or three people to 15, Hassabis said. "Go is a pretty sizable project for us," he said. DeepMind recently hired Matthew Lai, a London researcher who developed a system capable of playing chess at the grandmaster level. His software was able to reason in a way similar to how humans do, a more efficient method than IBM's attempt to crunch every possible outcome before making a move in the 1990s.