{"id":9504,"date":"2017-10-05T14:25:29","date_gmt":"2017-10-05T14:25:29","guid":{"rendered":"https:\/\/rsoftsolution.com\/blog\/cardiologs-raises-6-4m-to-bring-image-recognition-to-ekg-analysis.html"},"modified":"2017-10-05T14:25:29","modified_gmt":"2017-10-05T14:25:29","slug":"cardiologs-raises-6-4m-to-bring-image-recognition-to-ekg-analysis","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/cardiologs-raises-6-4m-to-bring-image-recognition-to-ekg-analysis.html","title":{"rendered":"Cardiologs raises $6.4M to bring image recognition to EKG analysis"},"content":{"rendered":"


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You\u2019ll find image recognition technology in almost every kind of consumer service you would use today \u2014 like Facebook, Google, or any number of other apps \u2014 but Yann Fleureau is hoping that he can build a whole business off of its increasing success in healthcare.<\/p>\n

Fleureau hopes that his startup, Cardiologs<\/a>, can use image recognition to analyze an EKG and detect potential problems going forward. Though he says his family members have dealt with cardiovascular problems over time, Fleureau says the motivation was a business opportunity to apply emerging technology that is getting more and more accurate every day in a slice of the healthcare universe that hasn\u2019t seen a lot of movement yet.\u00a0The company said it has raised $6.4 million in new financing today.<\/p>\n

\u201cAt the end of the day, doctors don\u2019t really care about AI,\u201d Fleureau said. \u201cThey care about the patient, so the question is whether we move the needle for the patient. That\u2019s what the discussion was about. For them, AI is kind of nice, but they want to see tangible results.\u201d<\/p>\n

Doctors and specialists are trained to recognize any kind of aberrations in an EKG, which allows them to quickly identify if there are any abnormalities in how someone\u2019s heart is working. That can include something along the lines of arrhythmia \u2014 or improper beating of the heart \u2014 that could signal long-term complications. But like any engineer, Fleureau hopes to streamline the process of looking at hours of EKG data and make it easy to upload the information and get a quick analysis powered by a machine.<\/p>\n

It\u2019s the same kind of idea behind teaching a computer to detect a cat in a photo, but rather than just for typical consumer behavior (like searching for a new pair of shoes), that kind of image recognition is seeing a lot of new applications. While image recognition isn\u2019t perfect yet \u2014 and that\u2019s also wildly dependent on the data set that\u2019s available \u2014 Fleureau said that the company is upfront on its success rate just like any other company that has to go through the FDA to get into the hands of doctors.<\/p>\n

[relatedd_articles\u201dNo one has 100% accuracy, it\u2019s to have a match between what you claim and do,\u201d Fleureau said. \u201cBut if you say you have 95% accuracy you\u2019d better have the proof of claim. If something goes wrong and the FDA finds our you only have 90% accuracy, from that perspective the device framework enables this well.\u201d<\/p>\n

Fleureau says that the company has figured out a way to build a kind of defensibility based on its relationships with experts that can help pin down the best signals to improve their EKG analysis. Most machine learning startups \u2014 image recognition or otherwise \u2014 will live and die by their data sets and the ability to accurately create the rules that will define whether they are successful. The startup\u2019s success will also be a factor of getting into the hands of doctors and getting an increasing pool of data. Cardiologs works with larger medical device companies and providers to gain adoption, Fleureau said.<\/p>\n

To be fair, that has been movement in this area. Like any startup \u2014 especially in healthcare \u2014 Cardiologs\u00a0will face steep competition from all fronts. The obvious competitor is iRhythm, which similarly looks to analyze potential problems with heart patterns. In the end, if a product can diagnose a potential problem and, as Fleureau says, move the needle on the patient, it\u2019ll probably win in some way. Fleureau says he hopes by focusing on software and partnering with hardware manufacturers, Cardiologs will provide something easy to use for doctors that will hit widespread adoption.<\/p>\n

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Article source: http:\/\/feedproxy.google.com\/~r\/techcrunchIt\/~3\/XqkpjP4YKXY\/<\/p>","protected":false},"excerpt":{"rendered":"

You\u2019ll find image recognition technology in almost every kind of consumer service you would use today \u2014 like Facebook, Google, or any number of other apps \u2014 but Yann Fleureau <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[19],"tags":[25],"class_list":["post-9504","post","type-post","status-publish","format-standard","hentry","category-enterprise-software","tag-enterprise"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t