Dynamic Survival Analysis for Early Event Prediction

Dynamic Survival Analysis for Early Event Prediction

This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our rese...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2024-03
Hauptverfasser: Yèche, Hugo, Burger, Manuel, Veshchezerova, Dinara, Rätsch, Gunnar
Format: Artikel
Sprache:eng
Schlagworte:
Health care
Survival
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Yèche, Hugo
Burger, Manuel
Veshchezerova, Dinara
Rätsch, Gunnar
description This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our research demonstrates their ability to match EEP models on a time-step level and significantly improve event-level metrics through a new alarm prioritization scheme (up to 11% AuPRC difference). This approach represents a significant step forward in predictive healthcare, providing a more nuanced and actionable framework for early event prediction and management.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2969195027</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2969195027</sourcerecordid><originalsourceid>FETCH-proquest_journals_29691950273</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwcanMS8zNTFYILi0qyyxLzFFwzEvMqSzOLFZIyy9ScE0syqlUcC1LzStRCChKTclMLsnMz-NhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRUBziuONLM0sDS1NDYzMjYlTBQBPlzSZ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2969195027</pqid></control><display><type>article</type><title>Dynamic Survival Analysis for Early Event Prediction</title><source>Free E- Journals</source><creator>Yèche, Hugo ; Burger, Manuel ; Veshchezerova, Dinara ; Rätsch, Gunnar</creator><creatorcontrib>Yèche, Hugo ; Burger, Manuel ; Veshchezerova, Dinara ; Rätsch, Gunnar</creatorcontrib><description>This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our research demonstrates their ability to match EEP models on a time-step level and significantly improve event-level metrics through a new alarm prioritization scheme (up to 11% AuPRC difference). This approach represents a significant step forward in predictive healthcare, providing a more nuanced and actionable framework for early event prediction and management.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Health care ; Survival</subject><ispartof>arXiv.org, 2024-03</ispartof><rights>2024. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>776,780</link.rule.ids></links><search><creatorcontrib>Yèche, Hugo</creatorcontrib><creatorcontrib>Burger, Manuel</creatorcontrib><creatorcontrib>Veshchezerova, Dinara</creatorcontrib><creatorcontrib>Rätsch, Gunnar</creatorcontrib><title>Dynamic Survival Analysis for Early Event Prediction</title><title>arXiv.org</title><description>This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our research demonstrates their ability to match EEP models on a time-step level and significantly improve event-level metrics through a new alarm prioritization scheme (up to 11% AuPRC difference). This approach represents a significant step forward in predictive healthcare, providing a more nuanced and actionable framework for early event prediction and management.</description><subject>Health care</subject><subject>Survival</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mQwcanMS8zNTFYILi0qyyxLzFFwzEvMqSzOLFZIyy9ScE0syqlUcC1LzStRCChKTclMLsnMz-NhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRUBziuONLM0sDS1NDYzMjYlTBQBPlzSZ</recordid><startdate>20240319</startdate><enddate>20240319</enddate><creator>Yèche, Hugo</creator><creator>Burger, Manuel</creator><creator>Veshchezerova, Dinara</creator><creator>Rätsch, Gunnar</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20240319</creationdate><title>Dynamic Survival Analysis for Early Event Prediction</title><author>Yèche, Hugo ; Burger, Manuel ; Veshchezerova, Dinara ; Rätsch, Gunnar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_29691950273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Health care</topic><topic>Survival</topic><toplevel>online_resources</toplevel><creatorcontrib>Yèche, Hugo</creatorcontrib><creatorcontrib>Burger, Manuel</creatorcontrib><creatorcontrib>Veshchezerova, Dinara</creatorcontrib><creatorcontrib>Rätsch, Gunnar</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yèche, Hugo</au><au>Burger, Manuel</au><au>Veshchezerova, Dinara</au><au>Rätsch, Gunnar</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Dynamic Survival Analysis for Early Event Prediction</atitle><jtitle>arXiv.org</jtitle><date>2024-03-19</date><risdate>2024</risdate><eissn>2331-8422</eissn><abstract>This study advances Early Event Prediction (EEP) in healthcare through Dynamic Survival Analysis (DSA), offering a novel approach by integrating risk localization into alarm policies to enhance clinical event metrics. By adapting and evaluating DSA models against traditional EEP benchmarks, our research demonstrates their ability to match EEP models on a time-step level and significantly improve event-level metrics through a new alarm prioritization scheme (up to 11% AuPRC difference). This approach represents a significant step forward in predictive healthcare, providing a more nuanced and actionable framework for early event prediction and management.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2024-03
issn 2331-8422
language eng
recordid cdi_proquest_journals_2969195027
source Free E- Journals
subjects Health care
Survival
title Dynamic Survival Analysis for Early Event Prediction
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-10T18%3A19%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Dynamic%20Survival%20Analysis%20for%20Early%20Event%20Prediction&rft.jtitle=arXiv.org&rft.au=Y%C3%A8che,%20Hugo&rft.date=2024-03-19&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2969195027%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2969195027&rft_id=info:pmid/&rfr_iscdi=true