{"679949":{"#nid":"679949","#data":{"type":"event","title":"ISYE Statistics Seminar - Zhaohui Qin","body":[{"value":"\u003Cp\u003ETitle:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EA novel association study framework powered by machine learning\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EAbstract:\u0026nbsp;\u003C\/p\u003E\u003Cp\u003EGenome-wide association studies (GWASs) have been widely applied to discover genetic variants associated with a diverse array of traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on image-derived quantitative features, which are univariate. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying variants that lead to detectable discrepancies on the full-frame brain images. When applied to data collected by the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) consortium, we are able to identify novel variants that show strong association with brain phenotypes.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAbstract\u003C\/p\u003E\u003Cp\u003EGenome-wide association studies (GWASs) have been widely applied to discover genetic variants associated with a diverse array of traits. So far, almost all GWASs conducted in neuroimaging genetics are performed on image-derived quantitative features, which are univariate. In this study, we proposed and implemented a novel machine learning strategy for systematically identifying variants that lead to detectable discrepancies on the full-frame brain images. When applied to data collected by the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) consortium, we are able to identify novel variants that show strong association with brain phenotypes.\u003C\/p\u003E\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"A novel association study framework powered by machine learning"}],"uid":"36433","created_gmt":"2025-01-24 18:24:47","changed_gmt":"2025-01-24 18:27:09","author":"mrussell89","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2025-04-15T11:00:00-04:00","event_time_end":"2025-04-15T12:00:00-04:00","event_time_end_last":"2025-04-15T12:00:00-04:00","gmt_time_start":"2025-04-15 15:00:00","gmt_time_end":"2025-04-15 16:00:00","gmt_time_end_last":"2025-04-15 16:00:00","rrule":null,"timezone":"America\/New_York"},"location":"Groseclose 402","extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"177814","name":"Postdoc"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"},{"id":"78751","name":"Undergraduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}