{"id":2513,"date":"2017-05-25T16:55:34","date_gmt":"2017-05-25T23:55:34","guid":{"rendered":"https:\/\/www.microsoft.com\/industry\/blog\/uncategorized\/empowering-care-teams-machine-learning-insight\/"},"modified":"2023-05-31T16:37:40","modified_gmt":"2023-05-31T23:37:40","slug":"empowering-care-teams-machine-learning-insight","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/industry\/blog\/healthcare\/2017\/05\/25\/empowering-care-teams-machine-learning-insight\/","title":{"rendered":"Empowering care teams with machine-learning insight"},"content":{"rendered":"<p>We\u2019re excited that health will be a key focus at the Japan CityNext Forum coming up on May 30 in Tokyo. Stefan Sjoestroem, Vice President, Public Sector, Microsoft Asia, and Akira Sakakibara, Chief Technology Officer, Microsoft Japan, will kick off the event with a keynote on how health and government organizations around the world are digitally transforming and using our trusted cloud as a force for global good to help them address complex challenges.<\/p>\n<p>After the keynote, attendees can learn about real-world examples of digital transformation in the healthcare and government track case study sessions. We\u2019re thrilled that our partner <a href=\"http:\/\/www.kensci.com\/\" target=\"_blank\" rel=\"noopener\">KenSci<\/a> will be sharing how it\u2019s helping providers use machine learning to improve health outcomes and reduce costs as part of the healthcare track.<\/p>\n<p>KenSci customer <a href=\"http:\/\/www.fullertonhealth.com\/index.html\" target=\"_blank\" rel=\"noopener\">Fullerton Health<\/a> used advanced analytics and machine learning to immediately identify over a million dollars in fraudulent and questionable claims <a href=\"https:\/\/enterprise.microsoft.com\/en-us\/articles\/industries\/health\/saving-lives-money-with-machine-learning\/\" target=\"_blank\" rel=\"noopener\">as Tom Lawry wrote recently<\/a>. It also helped an employer reduce the costs of managing the health of an employee population with chronic conditions by 60 percent. Next up, Fullerton Health plans to apply machine learning to improve its evidence-based medicine initiative and help clinicians predict the next best step for a patient.<\/p>\n<p>In its session at the Japan CityNext Forum, KenSci will share how providers can identify population health risks, improve care outcomes, and streamline patient flow through the hospital with its <a href=\"https:\/\/appsource.microsoft.com\/en-us\/product\/web-apps\/kensci.4831168d-903c-4ac9-a2fc-75952624b577?tab=Overview\" target=\"_blank\" rel=\"noopener\">Clinical Analytics solution<\/a>. Usually providers only have the time and tools to look at a limited number of variables about a patient to determine a diagnosis and treatment. But machine learning can sift through oceans of data to bring valuable insights to the surface. With the right machine learning solution, providers can not only get a closer look at each patient\u2019s history, they can foresee future risks and get suggestions on how to provide the most effective care.<\/p>\n<p>Helping physicians prioritize time and make better-informed decisions is exactly what the KenSci Clinical Analytics solution is designed to do. The solution, built on <a href=\"https:\/\/enterprise.microsoft.com\/en-us\/articles\/industries\/health\/not-all-clouds-are-created-equal-check-the-facts-2\/\" target=\"_blank\" rel=\"noopener\">trusted Microsoft Cloud technology<\/a>, is the world\u2019s first vertically integrated machine learning platform for healthcare. It delivers risk predictions to providers in the context of their daily workflow, using machine learning models that mine millions of records from public and customer data sets\u2014like claims, EHR, ADT, financial, and patient-generated data. These insights can help clinicians base decisions on dynamic analysis that gets more precise every day.<\/p>\n<h2>Empower your care teams with machine learning\u2014starting now<\/h2>\n<p>The KenSci Clinical Analytics solution takes advantage of more than 180 pre-built machine learning models, delivering a substantial return on investment in <a href=\"http:\/\/www.kensci.com\/\" target=\"_blank\" rel=\"noopener\">just 12 weeks<\/a>. Plus, it integrates easily with existing EMR systems\u2014so care managers and care providers aren\u2019t slowed down by having to learn and use a separate interface.<\/p>\n<p>If you\u2019ll be at the <a href=\"https:\/\/www.microsoft.com\/ja-jp\/business\/publicsector\/cnsf2017.aspx\" target=\"_blank\" rel=\"noopener\">Japan CityNext Forum<\/a>, attend the healthcare track case study session #3 to learn more. You can also read about the solution in <a href=\"https:\/\/enterprise.microsoft.com\/en-us\/articles\/industries\/health\/fighting-death-data-science\/\" target=\"_blank\" rel=\"noopener\">this blog<\/a> by David Turcotte, Global Industry Director, Public Sector, Microsoft.<\/p>\n<p>And you can try the solution today on <a href=\"https:\/\/appsource.microsoft.com\/en-us\/product\/web-apps\/kensci.4831168d-903c-4ac9-a2fc-75952624b577?tab=Overview\" target=\"_blank\" rel=\"noopener\">Microsoft AppSource<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>At the Japan CityNext Forum, our partner KenSci will share how it\u2019s helping providers use machine learning to improve health outcomes and reduce costs.<\/p>\n","protected":false},"author":206,"featured_media":10407,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"categories":[1507],"post_tag":[],"content-type":[1488],"coauthors":[1580],"class_list":["post-2513","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-healthcare","content-type-events"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Empowering care teams with machine-learning insight - Microsoft Industry Blogs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.microsoft.com\/en-us\/industry\/blog\/healthcare\/2017\/05\/25\/empowering-care-teams-machine-learning-insight\/\" \/>\n<meta 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