{"page":"\u003clink rel=\"stylesheet\" href=\"https://lessonplanet.com/assets/packs/css/resources-c03aa079.css\" /\u003e\n\u003clink rel=\"stylesheet\" href=\"https://lessonplanet.com/assets/packs/css/lp_boclips_stylesheets-517835be.css\" media=\"all\" /\u003e\n\u003cdiv data-title='Artificial Intelligence defeats medics at neuroimaging' data-url='/boclips/videos/5c54d7d3d8eafeecae20f19c' data-video-url='/boclips/videos/5c54d7d3d8eafeecae20f19c' id='bo_player_modal'\u003e\n\u003cdiv class='boclips-resource-page modal-dialog panel-container'\u003e\n\u003cdiv class='react-notifications-root'\u003e\u003c/div\u003e\n\u003cdiv class='rp-header'\u003e\n\u003cdiv class='rp-type'\u003e\n\u003ci aria-hidden='true' class='fai fa-regular fa-circle-play'\u003e\u003c/i\u003e\nVideo\n\u003c/div\u003e\n\u003ch1 class='rp-title' id='video-title'\u003e\nArtificial Intelligence defeats medics at neuroimaging\n\u003c/h1\u003e\n\u003cdiv class='rp-actions'\u003e\n\u003cdiv class='mr-1'\u003e\n\u003ca class=\"btn btn-success\" data-posthog-event=\"Signup: LP Signup Activity\" data-posthog-location=\"body_link_boclips\" data-remote=\"true\" href=\"/subscription/new\"\u003e\u003cspan\u003e\u003cspan\u003eGet Free Access\u003c/span\u003e\u003cspan class=\"\"\u003e for 10 Days\u003c/span\u003e\u003cspan\u003e!\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class='rp-body'\u003e\n\u003cdiv class='rp-info'\u003e\n\u003cdiv aria-label='Hide resource details' class='rp-hide-info' role='button' tabindex='0'\u003e\u0026times;\u003c/div\u003e\n\u003ci aria-label='Expand resource details' class='rp-expand-info fai fa-solid fa-up-right-and-down-left-from-center' role='button' tabindex='0'\u003e\u003c/i\u003e\n\u003ci aria-label='Compress resource details' class='rp-compress-info fai fa-solid fa-down-left-and-up-right-to-center' role='button' tabindex='0'\u003e\u003c/i\u003e\n\u003cdiv class='rp-rating'\u003e\n\u003cspan class='resource-pool'\u003e\n\u003cspan class='pool-label'\u003ePublisher:\u003c/span\u003e\n\u003cspan class='pool-name'\u003e\n\u003cspan class='text'\u003e\u003ca data-publisher-id=\"30356011\" href=\"/search?publisher_ids%5B%5D=30356011\"\u003eCurated Video\u003c/a\u003e\u003c/span\u003e\n\u003c/span\u003e\n\u003c/span\u003e\n\u003c/div\u003e\n\u003cdiv class='rp-description'\u003e\n\u003cspan class='short-description'\u003eLEADIN\u0026nbsp;\u0026nbsp;              Artifical Intelligence has defeated a group of human doctors in a neuroimaging competition in Beijing.               In two rounds of competition, contestants raced to diagnose brain conditions by...\u003c/span\u003e\n\u003cspan class='full-description hide'\u003eLEADIN  \u003cbr/\u003e              Artifical Intelligence has defeated a group of human doctors in a neuroimaging competition in Beijing. \u003cbr/\u003e              In two rounds of competition, contestants raced to diagnose brain conditions by interpreting CT and MRI images. \u003cbr/\u003e              But the human doctors say there's still a lot for AI to learn. \u003cbr/\u003e              STORYLINE\u003cbr/\u003e              This is the world's first competition between physicians and artificial intelligence in neuroimaging. \u003cbr/\u003e              Human medics competed against AI to diagnose brain tumours and predict haemorrhage and cerebrovascular diseases by studying images of over 200 cases within the required time. \u003cbr/\u003e              The human team of 30 radiologists and neurological doctors lost to the neurological disease diagnostic AI system called BioMind. In both rounds the AI was 20 percent more accurate. \u003cbr/\u003e              BioMind was devised in the lab that was set up by the China National Clinical Research Center and Hanalytics Artificial Intelligence Research Centre for Neurological Diseases in the Beijing Tiantan Hospital, which specialises in treatment for neurological conditions. \u003cbr/\u003e              Developed with deep learning (machine based learning), BioMind was trained with tens of thousands of CT and MRI images of neurological disorder cases that were archived by Beijing Tiantan Hospital in the past decade to teach the system to recognize brain-related diseases on images and produce a preliminary diagnosis as the reference for doctors. \u003cbr/\u003e              The AI system aims at assisting doctors to reduce blind spots and misdiagnosis, and increasing doctors' efficiency, says Raymond Moh, CEO of Hanalytics. \u003cbr/\u003e              \"The entire process of diagnosis can take half an hour to close an hour to analyze thousands of images just for one patient alone. But the whole process can be automated all within a few seconds with artificial intelligence,\" Moh says. \u003cbr/\u003e              However Jing Lina, a radiologist from Beijing Tiantan Hospital on the losing human team, doubts the system could handle real-world complexities beyond the \"either-or questions\" of the competition.\u003cbr/\u003e              \"There are situations where two similar images indicate two different pathological features. We were not given any information about patients' medical history, which we can use for comprehensive diagnosis. We have nothing but the MRI images,\" says Jing a member of the human diagnostic team. \u003cbr/\u003e              \"One of the advantages that human doctors enjoy is that we have solid medical foundations and background with which we can make the comprehensive analysis. With all these information, I believe we have the chance to beat AI\" Jing adds. \u003cbr/\u003e              The medical demands of China's enormous population have stressed the supply of trained doctors. \u003cbr/\u003e              The government has turned to AI for a solution.\u003cbr/\u003e              The State Council, China's chief administrative authority, in July 2017 issued the \"Three-Year Action Plan for Promoting the Development of a New Generation of Artificial Intelligence (2018-2020)\", which proposed to establish a fast and accurate AI application system in medical care to upgrade medical service.\u003cbr/\u003e              In this country, every year, there is 40 percent increase of medical images. But the increment of radiologists is less than five percent. This gap is going to increase. You will never be able to address (the issue) by traditional IT solution. So AI is probably one of the only solution to close this gap. The problem is there is not enough radiologists and doctors to start with to be replaced, rather, AI itself is to fill this gap\" says Moh. \u003cbr/\u003e              BioMind has achieved an accuracy rate of around 90 percent in the diagnosis of common neurological diseases.\u003cbr/\u003e              Its developers are still working on the verification and validation, which is now mainly conducted by human doctors in the Beijing Tiantan hospital.\u003cbr/\u003e              Jin Jing, who works in the hospital's Neurology Center, says there is still more work to do before BioMind is ready to be integrated into the hospital's regular operations.\u003cbr/\u003e              \"There is a long way to go before practical application. Most importantly, the sample volume BioMind learns from has to be increased.\"\u003cbr/\u003e              Though it takes time for a new technology being accepted by the public, Jin found something else bothers him more: physicians might rely too much on the analysis given by BioMind to diagnose independently.\u003cbr/\u003e              \"I'm worried the AI development might interrupt our talent training system. The development of AI depends on highly talented medical professionals.\"\u003cbr/\u003e              Fang Weidong, a doctor from the Affiliated Hospital of Chongqing University of Medical Sciences with experience of 20 years in the neurological field, is not surprised the medics lost the competition. \u003cbr/\u003e              He is looking forward to integrating AI into daily work.\u003cbr/\u003e              \"I'm so tired! Very tired ! As I said, we have to deal with a hundred reports every day. It would be great if AI can help us filter the reports, produce a preliminary diagnosis, even complete a report, before I make a final diagnosis. In this way can I feel relaxed. I can't wait to work with AI !\" Fang says.\u003cbr/\u003e            \u003cbr/\u003e\u003cbr/\u003e              ASSOCIATED PRESS \u003cbr/\u003e              Beijing - 30 June 2018\u003cbr/\u003e              1.Wide of AI vs human doctors contest\u003cbr/\u003e              UPSOUND (Mandarin) Female host, \"Three, Two, One. Timing starts.\"\u003cbr/\u003e              2. Wide of BioMind system on stage\u003cbr/\u003e              3. Pan of computers with BioMind system\u003cbr/\u003e              4. Various of doctors in competition\u003cbr/\u003e              5. Mid of doctor checking CT image on computer\u003cbr/\u003e              6. Close of MRI image on computer\u003cbr/\u003e              7. SOUNDBITE (English) Raymond Moh, CEO of Hanalytics, who developed BioMind system in cooperation with Beijing Tiantan Hospital\u003cbr/\u003e              \"AI can also be used to generate reports. This report, it actually houses all the contents, for example, what outcome it is, why does it happen, automatically. We don't have a doctor type out from scratch. The entire process of diagnosis can take half an hour to close an hour to analyze thousands of images just for one patient scan alone. But the whole process can be automated all within a few seconds with artificial intelligence. So that's the power of artificial intelligence today, and what we can achieve with BioMind.\"\u003cbr/\u003e              8. Wide of competition\u003cbr/\u003e              9. Close of BioMind diagnostic system on computer\u003cbr/\u003e              10. Wide of doctors voting for answers\u003cbr/\u003e              11. Close of doctors discussing\u003cbr/\u003e              12. Various of contest outcome on big screen showing BioMind correctly predicted 83 percent of brain haemorrhage compared to 63 percent of the human group \u003cbr/\u003e              13. Wide of audience\u003cbr/\u003e              14. Wide of doctors \u003cbr/\u003e              15. Close of BioMind competition poster\u003cbr/\u003e              16. SOUNDBITE (Mandarin) Jing Lina, Radiologist, Tiantan Hospital\u003cbr/\u003e              \"There are situations where two similar images indicate two different pathological features. We were not given any information about patients' medical history nor CT images, which we can use for comprehensive diagnosis. We have nothing but the MRI images. One of the advantages that human doctors enjoy is that we have solid medical foundations or background with which we can make the comprehensive analysis. With all this information, I believe we have the chance to beat AI.\"\u003cbr/\u003e              17. Wide of audience\u003cbr/\u003e              18. Wide of screen showing doctors in competition\u003cbr/\u003e              19. Various of doctor reading MRI images on computer\u003cbr/\u003e              20.  SOUNDBITE (English) Raymond Moh, CEO of Hanalytics, who developed BioMind system in cooperation with Beijing Tiantan Hospital\u003cbr/\u003e              \"In fact, the statistics speak for itself. In this country, every year, there is 40 percent increase of medical images. But the increment of the number of radiologists is less than five percent. This gap is going to increase. You will never be able to address (the issue) by traditional IT solution. So AI is probably one of the only solution to close this gap. The problem is there is not enough radiologists and doctors to start with to be replaced, rather, AI itself is used to fill this gap.\"\u003cbr/\u003e              ASSOCIATED PRESS \u003cbr/\u003e              Beijing – 4 July 2018\u003cbr/\u003e              21. Exterior of Beijing Tiantan Hospital\u003cbr/\u003e              22. Various of brand of China National Clinical Research Center for Neurological Diseases\u003cbr/\u003e              23. Wide of AI lab\u003cbr/\u003e              24. Wide of doctor Jin Jing talking with colleagues\u003cbr/\u003e              25. Close of image on computer\u003cbr/\u003e              26. SOUNDBITE (Mandarin) Jin Jing, Doctor at Neurology Center of Beijing Tiantan Hospital\u003cbr/\u003e              \"Firstly, it (BioMind) needs more verification and validation. Secondly, it needs more deep learning. Thirdly, it needs to be reviewed by ethics and relevant policies and regulations. So there is a long way to go before practical application. Most importantly, the sample volume which BioMind learns from has to be increased. This is its main development direction.\"\u003cbr/\u003e              27. Pan from computer to Jin Jing and his colleague\u003cbr/\u003e              28. Close of images on computer\u003cbr/\u003e              29. SOUNDBITE (Mandarin) Jin Jing, doctor of Neurology Centre of Beijing Tiantan Hospital\u003cbr/\u003e              \"I'm worried the AI development might interrupt our talent training system. The development of AI actually depends on highly talented medical professionals. Without them, who will AI learn from, right ?\"\u003cbr/\u003e              ASSOCIATED PRESS \u003cbr/\u003e              Beijing - 30 June 2018\u003cbr/\u003e              30. Wide of BioMind system on stage\u003cbr/\u003e              31. Wide of doctors in competition\u003cbr/\u003e              32. Wide of Doctor Fang Weidong being interviewed by host\u003cbr/\u003e              33. SOUNDBITE (Mandarin) Fang Weidong, Doctor at Affiliated Hospital of Chongqing University of Medical Sciences\u003cbr/\u003e              \"I have worked for twenty years. I sincerely wish AI could come as early as possible, so I can be relieved. I'm so tired ! Really tired ! As I said, we have to write about a hundred reports every day. It would be great if AI can help us filter the reports, come up with preliminary diagnosis, even complete a report, before I make a final diagnosis. In this way can I feel relaxed. I can't wait to work with AI !\"\u003cbr/\u003e              34. Various of judges detecting images\u003cbr/\u003e              35. 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