MACHINE LEARNING PLATFORM FOR GENERATING RISK MODELS
The disclosed embodiments concern methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models. In some implementations, a fully automated process is provided that allows for a PRS model to be defined by an initial set of parameters. In some implementat...
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| creator | SURESH, SANJEEV MARSHALL, AUSTIN WILLIAM AMIRI, SHIVA KOELSCH, BERTRAM LORENZ ZHAN, JIANAN HAMILTON, SHANNON M GANESAN, MANOJ SINHA, SUBARNAREKHA POLCARI, MICHAEL MACPHERSON, JOHN MICHAEL KONDO, DERRICK POO-RAY ASHENHURST, JAMES ROWAN BLAKKAN, CORDELL T |
| description | The disclosed embodiments concern methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models. In some implementations, a fully automated process is provided that allows for a PRS model to be defined by an initial set of parameters. In some implementations the PRS models are trained to provide a PRS for particular populations.
Les modes de réalisation de l'invention concernent des procédés, un appareil, des systèmes et des produits programmes d'ordinateur pour développer des modèles de score de risque polygénique (PRS). Dans certains modes de réalisation, l'invention concerne un procédé entièrement automatisé qui permet de définir un modèle de PRS au moyen d'un ensemble initial de paramètres. Dans certains modes de réalisation, les modèles de PRS sont entraînés pour fournir un PRS pour des populations particulières. |
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Les modes de réalisation de l'invention concernent des procédés, un appareil, des systèmes et des produits programmes d'ordinateur pour développer des modèles de score de risque polygénique (PRS). Dans certains modes de réalisation, l'invention concerne un procédé entièrement automatisé qui permet de définir un modèle de PRS au moyen d'un ensemble initial de paramètres. Dans certains modes de réalisation, les modèles de PRS sont entraînés pour fournir un PRS pour des populations particulières.</description><language>eng ; fre</language><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; PHYSICS</subject><creationdate>2021</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211202&DB=EPODOC&CC=CA&NR=3179983A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76418</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20211202&DB=EPODOC&CC=CA&NR=3179983A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>SURESH, SANJEEV</creatorcontrib><creatorcontrib>MARSHALL, AUSTIN WILLIAM</creatorcontrib><creatorcontrib>AMIRI, SHIVA</creatorcontrib><creatorcontrib>KOELSCH, BERTRAM LORENZ</creatorcontrib><creatorcontrib>ZHAN, JIANAN</creatorcontrib><creatorcontrib>HAMILTON, SHANNON M</creatorcontrib><creatorcontrib>GANESAN, MANOJ</creatorcontrib><creatorcontrib>SINHA, SUBARNAREKHA</creatorcontrib><creatorcontrib>POLCARI, MICHAEL</creatorcontrib><creatorcontrib>MACPHERSON, JOHN MICHAEL</creatorcontrib><creatorcontrib>KONDO, DERRICK POO-RAY</creatorcontrib><creatorcontrib>ASHENHURST, JAMES ROWAN</creatorcontrib><creatorcontrib>BLAKKAN, CORDELL T</creatorcontrib><title>MACHINE LEARNING PLATFORM FOR GENERATING RISK MODELS</title><description>The disclosed embodiments concern methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models. In some implementations, a fully automated process is provided that allows for a PRS model to be defined by an initial set of parameters. In some implementations the PRS models are trained to provide a PRS for particular populations.
Les modes de réalisation de l'invention concernent des procédés, un appareil, des systèmes et des produits programmes d'ordinateur pour développer des modèles de score de risque polygénique (PRS). Dans certains modes de réalisation, l'invention concerne un procédé entièrement automatisé qui permet de définir un modèle de PRS au moyen d'un ensemble initial de paramètres. Dans certains modes de réalisation, les modèles de PRS sont entraînés pour fournir un PRS pour des populations particulières.</description><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2021</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDDxdXT28PRzVfBxdQzy8_RzVwjwcQxx8w_yVQASCu6ufq5BjiEg8SDPYG8FX38XV59gHgbWtMSc4lReKM3NoODmGuLsoZtakB-fWlyQmJyal1oS7-xobGhuaWlh7GhoTIQSAHE8JuM</recordid><startdate>20211202</startdate><enddate>20211202</enddate><creator>SURESH, SANJEEV</creator><creator>MARSHALL, AUSTIN WILLIAM</creator><creator>AMIRI, SHIVA</creator><creator>KOELSCH, BERTRAM LORENZ</creator><creator>ZHAN, JIANAN</creator><creator>HAMILTON, SHANNON M</creator><creator>GANESAN, MANOJ</creator><creator>SINHA, SUBARNAREKHA</creator><creator>POLCARI, MICHAEL</creator><creator>MACPHERSON, JOHN MICHAEL</creator><creator>KONDO, DERRICK POO-RAY</creator><creator>ASHENHURST, JAMES ROWAN</creator><creator>BLAKKAN, CORDELL T</creator><scope>EVB</scope></search><sort><creationdate>20211202</creationdate><title>MACHINE LEARNING PLATFORM FOR GENERATING RISK MODELS</title><author>SURESH, SANJEEV ; MARSHALL, AUSTIN WILLIAM ; AMIRI, SHIVA ; KOELSCH, BERTRAM LORENZ ; ZHAN, JIANAN ; HAMILTON, SHANNON M ; GANESAN, MANOJ ; SINHA, SUBARNAREKHA ; POLCARI, MICHAEL ; MACPHERSON, JOHN MICHAEL ; KONDO, DERRICK POO-RAY ; ASHENHURST, JAMES ROWAN ; BLAKKAN, CORDELL T</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CA3179983A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre</language><creationdate>2021</creationdate><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>SURESH, SANJEEV</creatorcontrib><creatorcontrib>MARSHALL, AUSTIN WILLIAM</creatorcontrib><creatorcontrib>AMIRI, SHIVA</creatorcontrib><creatorcontrib>KOELSCH, BERTRAM LORENZ</creatorcontrib><creatorcontrib>ZHAN, JIANAN</creatorcontrib><creatorcontrib>HAMILTON, SHANNON M</creatorcontrib><creatorcontrib>GANESAN, MANOJ</creatorcontrib><creatorcontrib>SINHA, SUBARNAREKHA</creatorcontrib><creatorcontrib>POLCARI, MICHAEL</creatorcontrib><creatorcontrib>MACPHERSON, JOHN MICHAEL</creatorcontrib><creatorcontrib>KONDO, DERRICK POO-RAY</creatorcontrib><creatorcontrib>ASHENHURST, JAMES ROWAN</creatorcontrib><creatorcontrib>BLAKKAN, CORDELL T</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>SURESH, SANJEEV</au><au>MARSHALL, AUSTIN WILLIAM</au><au>AMIRI, SHIVA</au><au>KOELSCH, BERTRAM LORENZ</au><au>ZHAN, JIANAN</au><au>HAMILTON, SHANNON M</au><au>GANESAN, MANOJ</au><au>SINHA, SUBARNAREKHA</au><au>POLCARI, MICHAEL</au><au>MACPHERSON, JOHN MICHAEL</au><au>KONDO, DERRICK POO-RAY</au><au>ASHENHURST, JAMES ROWAN</au><au>BLAKKAN, CORDELL T</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MACHINE LEARNING PLATFORM FOR GENERATING RISK MODELS</title><date>2021-12-02</date><risdate>2021</risdate><abstract>The disclosed embodiments concern methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models. In some implementations, a fully automated process is provided that allows for a PRS model to be defined by an initial set of parameters. In some implementations the PRS models are trained to provide a PRS for particular populations.
Les modes de réalisation de l'invention concernent des procédés, un appareil, des systèmes et des produits programmes d'ordinateur pour développer des modèles de score de risque polygénique (PRS). Dans certains modes de réalisation, l'invention concerne un procédé entièrement automatisé qui permet de définir un modèle de PRS au moyen d'un ensemble initial de paramètres. Dans certains modes de réalisation, les modèles de PRS sont entraînés pour fournir un PRS pour des populations particulières.</abstract><oa>free_for_read</oa></addata></record> |
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| title | MACHINE LEARNING PLATFORM FOR GENERATING RISK MODELS |
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