{"id":467,"date":"2019-01-23T10:30:36","date_gmt":"2019-01-23T10:30:36","guid":{"rendered":"http:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/?p=467"},"modified":"2019-01-23T10:30:36","modified_gmt":"2019-01-23T10:30:36","slug":"westminster-phd-student-leads-the-stfc-global-challenge-network-impactful-health-data-analytics","status":"publish","type":"post","link":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/westminster-phd-student-leads-the-stfc-global-challenge-network-impactful-health-data-analytics\/","title":{"rendered":"Westminster PhD Student Leads The STFC Global Challenge Network Impactful Health Data Analytics"},"content":{"rendered":"<p>Mahmoud Aldraimli, a PhD researcher from the School of Computer Science and Engineering, successfully led a group of experts to build machine learning models to assist in the prediction of toxicities in breast cancer data.\n<\/p>\n<p>Hosted by the University of Manchester, the Radiotherapy Machine Learning network event was the first of its kind, a joint initiative with the NCRI Clinical and Translational Radiotherapy (CTRad) group. It brought together cancer clinicians and experts from the Machine Learning community to address challenges in cancer radiotherapy to build high-quality outputs.\n<\/p>\n<p>Mahmoud succeeded in the competitive selection process and secured a place in the event as a Machine Learning Expert. He started his PhD studies on \u201cBuilding Machine Learning Models for Breast Cancer Risk Prediction\u201d in October 2017 and is supervised by Dr Daniel Soria and Professor Thierry Chaussalet from the School of Computer Science and Engineering, and Dr Miriam Dwek from the School of Life Sciences. He is a member of the Health and Social Care Modelling Group, of the Cancer Research Group and works actively within the newly formed Health Innovation Ecosystem at the University of Westminster.<\/p>\n<p><a href=\"https:\/\/www.westminster.ac.uk\/news-and-events\/news\/2019\/westminster-phd-student-leads-experts-at-the-stfc-global-challenge-network-event-in-advanced-radiotherapy\">Original article<\/a> on the University of Westminster Website<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mahmoud Aldraimli, a PhD researcher from the School of Computer Science and Engineering, successfully led a group of experts to build machine learning models to assist in the prediction of toxicities in breast cancer data. Hosted by the University of Manchester, the Radiotherapy Machine Learning network event was the first of its kind, a joint [&hellip;]<\/p>\n","protected":false},"author":79,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-467","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/posts\/467","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/users\/79"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/comments?post=467"}],"version-history":[{"count":0,"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/posts\/467\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/media?parent=467"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/categories?post=467"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.westminster.ac.uk\/healthinnovationecosystem\/wp-json\/wp\/v2\/tags?post=467"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}