The takeaway from all these recent A.I

The takeaway from all these recent A.I

The takeaway from all these recent A.I. Oakden-Rayner questioned the need a.i. FOR MORE tech must Fortune: How coronavirus stimulus plan would change the workers’ benefit concert Zoom continuous meetings to get hacked. In addition the error base IA bites Hospitals are low on the most critical supply everything: Listen oxygen Leadership Next, a review of Fortune podcast changing role of general managers WATCH: The best earphones in 2020: Apple AirPods Pro vs. But this deep learning system was probably formed on skewed data. In general, more accurate and complete data sets are more useful, Oakden-Rayner said in an email toFortune. Just Covid detected on CT-19 is unlikely to be useful, said Oakden Rayner in the email. He also questioned a high-tech industry is scrambling to develop and sell A. I. Read: thermal-imaging tech is on the rise. Apaper published in March in the medical journal BMJ found that many of these studies exaggerated their findings, which A. I. Can it help against coronavirus? In a paper Oakden-Rayner noted that researchers have developed a learning system towards recognizing coronavirus based on data from 1,014 patients at Tongji University in Shanghai. Nagendran, an academic clinical fellow of the National Institute of Health Research U.K.s, says studies describing the superiority A.I.s human doctors can deceive people. Artificial intelligence is better in the analysis of medical images for diseases such as pneumonia and skin cancer that doctors are, in a number of academic papers. The review found 77 studies that lacked randomized trials included specific comments in their abstracts, or summaries, comparing their AI Theres been a lot of hype out there, and that can very quickly result in the media in stories that patients hear, saying things like, is just around the corner, the AI ​​the conclusion also includes thecurrent coronavirus pandemic, which has claimed more than 30,000 lives in the United States LukeOakden-Rayner, Director medical imaging research at the Royal Adelaide hospital in Australia, noticed a similar problem when heexamined few articles recently published on the use deep learning to diagnose Covid-19 by chest CT. How to prevent bombing Zoom Why China’s fight against tech-based coronavirus can be unpleasant in the US One of the main problems of these documents is that theres an artificial, artificial nature of many of these studies in which researchers essentially argue that their technology has outperformed a doctor, says Eric Topol, one of the BMJ papers authors and the founder and director of Scripps nonprofit translational research goal Institute.Its absurd to compare a AIs performance to that of doctors of man, he says, because in the real world, the choice between an AI more conventional test tools are increasingly distributed around the world, making them more available than CT scans, which are more expensive, Topol says. selection There’s this kind of nutty inclination to pit machine against doctors, and it’s really a consistent flaw because its going to be not only the machines that make medical image reading, said Topol. Topol agrees with Oakden-Rayner, saying it may be useful to have a review of the algorithm of a lung scan to see if they are potentially related Covid, but you really do need a to scan. You can not just go ahead right a prospective, Topol said about a more formal type of university that generally follows the preliminary research. The recent BMJ reviewed nearly 100 studies of a type of artificial intelligence called deep learning that had been used on medical tests of various disorders, including macular degeneration, tuberculosis, and several types of cancer. Topol says, the point Im just coming is if you look at these papers, the great majority90% are comparing man versus the machine, and it really was not necessary to do so. No disrespect to risk capitalistsobviously they’re an important part of the funding process for a lot of this innovationbut obviously their enthusiasm is always trying to make things happen on the market as quickly as possible, said Myura Nagendran, co-author of the paper BMJ. researchers even publish documents on the use of deep learning to diagnose coronavirus, explaining that the current test is already effective and that there are more important jobs AI These are essentially preliminary search of documents that highlight the potential uses of AI as defective medical imaging studies that the BMJ paper describes the coronavirus related documents have based their findings on a limited amount of data that was not representative of the whole population, that’s a problem known as selection bias. Medical imaging studies is that people should use skepticism to consider their results, Topol said. If there is a bottleneck that AI against the man, one of the big problems is that these documents will follow generally the most robust reporting standards that health professionals have tried to do the standard during the last decade, said Nagendran. Some researchers argue that they’ve developed A.I. in the current health care system, but researchers still need deeper clinical trials to test the effectiveness of technologys. analysis technology to medical imaging. system performance to that of human doctors.Of those, 23 said their A.I. The same technology would be unlikely to work well with people who have Covid-19, but have no symptoms in their lungs. These patients were diagnosed as having Covid-19 via conventional smear tests used to detect the disease; they also had the chest CT scans to see if there was an infection in the lungs. Doctors probably suspected patients had lung problems Covid-19, which is why they ordered CT chests of patients. can solve in the flow of medical work, data for this task will specifically be collected. systems that are faster than humans in the review chest CT scans to Covid-19 infections


Comments are closed.