{"id":788939,"date":"2021-10-26T23:52:20","date_gmt":"2021-10-27T06:52:20","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&p=788939"},"modified":"2022-01-26T16:12:05","modified_gmt":"2022-01-27T00:12:05","slug":"precision-medicine","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/precision-medicine\/","title":{"rendered":"Precision Medicine"},"content":{"rendered":"
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Precision Medicine<\/h1>\n\n\n\n

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Medical forecasting is a fundamental ingredient of intelligent health. We study a full life-circle forecasting task, including the prevention, diagnosis, monitoring, and treatment. Our research covers both epidemic diseases and chronic diseases. We leverage the power of machine learning and deep learning models to better predict the epidemic trends, patients\u2019 health conditions and treatment effects etc. Meanwhile, we design various models to handle the unique challenges in the medical filed, including the poor data quality, inherent data selection bias etc.<\/p>\n\n\n\n

Precision medicine is a promising research direction in healthcare, which transforms the way of diagnosis and treatment from conventional one-size-fits-all to target-the-right-diagnosis\/treatment-to-the-right-patients-at-the-right-time. It has already achieved great success on several clinical applications (e.g., reducing drug side effects and targeted therapy for cancers). Furthermore, the development of sequencing techniques and the large-scale of clinical data bring much more potentials to precision medicine.<\/p>\n\n\n\n

Our goal is to exploit the value of medical records and machine learning techniques, build an accurate and robust medical forecasting platform, that can be widely applied to the general clinical data to support the clinical decision making and treatment.<\/p>\n\n\n\n\n\n

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Medical forecasting is a fundamental ingredient of intelligent health. We study a full life-circle forecasting task, including the prevention, diagnosis, monitoring, and treatment. Our research covers both epidemic diseases and chronic diseases. We leverage the power of machine learning and deep learning models to better predict the epidemic trends, patients\u2019 health conditions and treatment effects […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13556,13553],"msr-locale":[268875],"msr-impact-theme":[261673],"msr-pillar":[],"class_list":["post-788939","msr-project","type-msr-project","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-medical-health-genomics","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Rui Wang","user_id":39880,"people_section":"Section name 0","alias":"ruiwa"}],"msr_research_lab":[199560],"msr_impact_theme":["Health"],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/788939"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":3,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/788939\/revisions"}],"predecessor-version":[{"id":815677,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/788939\/revisions\/815677"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=788939"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=788939"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=788939"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=788939"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=788939"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}