{"id":"https://openalex.org/W2115953433","doi":null,"title":"Parsing epileptic events using a Markov switching process model for correlated time series","display_name":"Parsing epileptic events using a Markov switching process model for correlated time series","publication_year":2013,"publication_date":"2013-02-13","ids":{"openalex":"https://openalex.org/W2115953433","mag":"2115953433"},"language":"en","primary_location":{"id":"mag:2115953433","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v28/wulsin13.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090802100","display_name":"Drausin Wulsin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Drausin Wulsin","raw_affiliation_strings":["Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA#TAB#","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068568859","display_name":"Emily B. Fox","orcid":"https://orcid.org/0000-0003-3188-9685","observed_orcids":["https://orcid.org/0000-0003-3188-9685"]},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emily B. Fox","raw_affiliation_strings":["Department of Statistics, University of Washington, Seattle, WA, USA"],"raw_orcid":"https://orcid.org/0000-0003-3188-9685","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017821899","display_name":"Brian Litt","orcid":"https://orcid.org/0000-0003-2732-6927","observed_orcids":["https://orcid.org/0000-0003-2732-6927"]},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brian Litt","raw_affiliation_strings":["Depts. of Neurology and Bioengineering, University of Pennsylvania, Philadelphia, PA USA"],"raw_orcid":"https://orcid.org/0000-0003-2732-6927","affiliations":[{"raw_affiliation_string":"Depts. of Neurology and Bioengineering, University of Pennsylvania, Philadelphia, PA USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.4478,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.98650794,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"356","last_page":"364"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10094","display_name":"Epilepsy research and treatment","score":0.36890000104904175,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Clinical Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10094","display_name":"Epilepsy research and treatment","score":0.36890000104904175,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Clinical Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.3544999957084656,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.1088000014424324,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/epilepsy","display_name":"epilepsy","score":0.9639999866485596},{"id":"https://openalex.org/keywords/clinical-seizures","display_name":"clinical seizures","score":0.9359999895095825},{"id":"https://openalex.org/keywords/intracranial-eeg","display_name":"intracranial EEG","score":0.9399999976158142},{"id":"https://openalex.org/keywords/nonparametric-bayesian-inference","display_name":"Bayesian nonparametrics","score":0.878000020980835},{"id":"https://openalex.org/keywords/correlated-time-series","display_name":"correlated time series","score":0.7559999823570251},{"id":"https://openalex.org/keywords/dynamical-regimes","display_name":"dynamical regimes","score":0.7670000195503235},{"id":"https://openalex.org/keywords/out-of-sample-forecasting","display_name":"out-of-sample forecasting","score":0.8019999861717224}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7243139743804932},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6339603662490845},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.5618607401847839},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4926627278327942},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.47687870264053345},{"id":"https://openalex.org/C2778186239","wikidata":"https://www.wikidata.org/wiki/Q41571","display_name":"Epilepsy","level":2,"score":0.43477416038513184},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4321502149105072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3950127065181732},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.19176247715950012},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.14720726013183594},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2115953433","doi":null,"is_oa":false,"landing_page_url":"http://proceedings.mlr.press/v28/wulsin13.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306419644","display_name":"International Conference on Machine Learning","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"International Conference on Machine Learning","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1517266559","https://openalex.org/W1528056001","https://openalex.org/W1840902794","https://openalex.org/W2004235096","https://openalex.org/W2008561984","https://openalex.org/W2009902427","https://openalex.org/W2011760672","https://openalex.org/W2012328630","https://openalex.org/W2019963883","https://openalex.org/W2031038564","https://openalex.org/W2078574541","https://openalex.org/W2109957730","https://openalex.org/W2110132815","https://openalex.org/W2113656889","https://openalex.org/W2118036030","https://openalex.org/W2118127869","https://openalex.org/W2128002512","https://openalex.org/W2143776609","https://openalex.org/W2158266063","https://openalex.org/W2169895393","https://openalex.org/W2170187757","https://openalex.org/W2242804882","https://openalex.org/W2728974037"],"related_works":["https://openalex.org/W7095373897","https://openalex.org/W2015875947","https://openalex.org/W74858052","https://openalex.org/W7098102648","https://openalex.org/W4404449807","https://openalex.org/W1964434285","https://openalex.org/W4308430540","https://openalex.org/W3211569561","https://openalex.org/W2506504742","https://openalex.org/W2886780705"],"abstract_inverted_index":{"Patients":[0],"with":[1],"epilepsy":[2],"can":[3,77,164],"manifest":[4],"short,":[5],"sub-clinical":[6,176],"epileptic":[7,50],"\\bursts":[8],"in":[9,146],"addition":[10],"to":[11,46],"full-blown":[12],"clinical":[13,167,180],"seizures.":[14,39,181],"We":[15,81,113,139,154],"believe":[16],"the":[17,33,60,68,71,123,132,136,141,173],"relationship":[18],"between":[19,79,96,122],"these":[20,48],"two":[21],"classes":[22],"of":[23,38,42,75,100,110,120,143,151,169,175],"events|something":[24],"not":[25],"previously":[26],"studied":[27],"quantitatively|could":[28],"yield":[29],"important":[30],"insights":[31],"into":[32,52],"nature":[34],"and":[35,73,105,117,148,171,178],"intrinsic":[36],"dynamics":[37],"A":[40,56],"goal":[41],"our":[43,157],"work":[44],"is":[45,67],"parse":[47],"complex":[49],"events":[51],"distinct":[53],"dynamic":[54,94,111],"regimes.":[55,112],"challenge":[57],"posed":[58],"by":[59],"intracranial":[61],"EEG":[62],"(iEEG)":[63],"data":[64],"we":[65],"study":[66],"fact":[69],"that":[70,89,156,163],"number":[72],"placement":[74],"electrodes":[76],"vary":[78],"patients.":[80],"develop":[82],"a":[83,97,115,126],"Bayesian":[84],"nonparametric":[85],"Markov":[86],"switching":[87],"process":[88,134],"allows":[90],"for":[91,131],"(i)":[92],"shared":[93],"regimes":[95],"variable":[98],"numbers":[99],"channels,":[101],"(ii)":[102],"asynchronous":[103],"regimeswitching,":[104],"(iii)":[106],"an":[107],"unknown":[108],"dictionary":[109],"encode":[114],"sparse":[116],"changing":[118],"set":[119],"dependencies":[121],"channels":[124],"using":[125],"Markov-switching":[127],"Gaussian":[128],"graphical":[129],"model":[130,145,158],"innovations":[133],"driving":[135],"channel":[137],"dynamics.":[138],"demonstrate":[140],"importance":[142],"this":[144],"parsing":[147],"out-of-sample":[149],"predictions":[150],"iEEG":[152],"data.":[153],"show":[155],"produces":[159],"intuitive":[160],"state":[161],"assignments":[162],"help":[165],"automate":[166],"analysis":[168],"seizures":[170],"enable":[172],"comparison":[174],"bursts":[177],"full":[179]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2016-06-24T00:00:00"}
