{"id":793523,"date":"2021-11-16T08:00:57","date_gmt":"2021-11-16T16:00:57","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&#038;p=793523"},"modified":"2021-11-16T12:33:37","modified_gmt":"2021-11-16T20:33:37","slug":"panel-discussion-experiments-models-inference-and-algorithms-learning-from-experts-who-do-it-all","status":"publish","type":"msr-video","link":"https:\/\/www.microsoft.com\/en-us\/research\/video\/panel-discussion-experiments-models-inference-and-algorithms-learning-from-experts-who-do-it-all\/","title":{"rendered":"Panel: Experiments, models, inference and algorithms: Learning from experts who do it all"},"content":{"rendered":"<p>Research in computational biology and healthcare benefits from the tight integration of data generation, model specification, and inference or learning. Many machine learning (ML) applications in these fields require data that is very expensive and\/or requires an expert to acquire, have access to only small datasets, and target end-use in high-risk settings. These challenges lead to a greater importance of multidisciplinary teams and skills that inform the joint development of experimental data and computational approaches. Recent examples show the power of integration for achieving research impact while applications without integration serve as cautionary tales. In this talk, we give a brief description of exemplary project-combining experiments and computation, followed by a panel discussion on the difficulties and best practices surrounding these projects.<\/p>\n<p>Learn more about the 2021 Microsoft Research Summit: <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/Aka.ms\/researchsummit\">https:\/\/Aka.ms\/researchsummit<span class=\"sr-only\"> (opens in new tab)<\/span><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Research in computational biology and healthcare benefits from the tight integration of data generation, model specification, and inference or learning. Many machine learning (ML) applications in these fields require data that is very expensive and\/or requires an expert to acquire, have access to only small datasets, and target end-use in high-risk settings. These challenges lead [&hellip;]<\/p>\n","protected":false},"featured_media":793607,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13553],"msr-video-type":[261275,261263],"msr-locale":[268875],"msr-post-option":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-793523","msr-video","type-msr-video","status-publish","has-post-thumbnail","hentry","msr-research-area-medical-health-genomics","msr-video-type-health-life-sciences-discovery","msr-video-type-research-summit-2021","msr-locale-en_us"],"msr_download_urls":"","msr_external_url":"https:\/\/youtu.be\/HqPcN5Chh2g","msr_secondary_video_url":"","msr_video_file":"","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/793523"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-video"}],"version-history":[{"count":5,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/793523\/revisions"}],"predecessor-version":[{"id":796666,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video\/793523\/revisions\/796666"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/793607"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=793523"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=793523"},{"taxonomy":"msr-video-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-video-type?post=793523"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=793523"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=793523"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=793523"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=793523"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}