{"id":"https://openalex.org/W5813897","doi":null,"title":"Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoning.","display_name":"Diagnosing Lyme disease - Tailoring patient specific Bayesian networks for temporal reasoning.","publication_year":2006,"publication_date":"2006-01-01","ids":{"openalex":"https://openalex.org/W5813897","mag":"5813897"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.145.4661","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.4661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.utia.cas.cz/files/mtr/pgm06/35_paper.pdf","raw_type":"text"},"volume":null,"type":"article","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/A5080465910","display_name":"Kristian G. Olesen","orcid":"https://orcid.org/0000-0002-4622-9578","observed_orcids":["https://orcid.org/0000-0002-4622-9578"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kristian G. Olesen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4622-9578","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023147094","display_name":"Ole Kristian Hejlesen","orcid":"https://orcid.org/0000-0003-3578-8750","observed_orcids":["https://orcid.org/0000-0003-3578-8750"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ole Hejlesen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3578-8750","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007573133","display_name":"Ram Benny Dessau","orcid":"https://orcid.org/0000-0002-1497-6309","observed_orcids":["https://orcid.org/0000-0002-1497-6309"]},"institutions":[{"id":"https://openalex.org/I4210099572","display_name":"N\u00e6stved Sygehus","ror":"https://ror.org/011dagb24","country_code":"DK","type":"healthcare","lineage":["https://openalex.org/I2799668677","https://openalex.org/I2802567020","https://openalex.org/I4210099572"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Ram Benny Dessau","raw_affiliation_strings":["N\u00e6stved Hospital"],"raw_orcid":"https://orcid.org/0000-0002-1497-6309","affiliations":[{"raw_affiliation_string":"N\u00e6stved Hospital","institution_ids":["https://openalex.org/I4210099572"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009852296","display_name":"Ivan Beltoft","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ivan Beltoft","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5016974245","display_name":"Michael Trangeled","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Michael Trangeled","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.00099075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":92},"biblio":{"volume":null,"issue":null,"first_page":"231","last_page":"238"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.6478999853134155,"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"}},"topics":[{"id":"https://openalex.org/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.6478999853134155,"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"}},{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.2768999934196472,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12574","display_name":"Clinical Reasoning and Diagnostic Skills","score":0.012900000438094139,"subfield":{"id":"https://openalex.org/subfields/2714","display_name":"Family Practice"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lyme-disease","display_name":"Lyme disease","score":0.9350000023841858},{"id":"https://openalex.org/keywords/bayesian-networks","display_name":"Bayesian networks","score":0.9539999961853027},{"id":"https://openalex.org/keywords/temporal-reasoning","display_name":"temporal reasoning","score":0.8190000057220459},{"id":"https://openalex.org/keywords/patient-specific-models","display_name":"patient-specific models","score":0.578000009059906},{"id":"https://openalex.org/keywords/medical-history","display_name":"medical history","score":0.6579999923706055},{"id":"https://openalex.org/keywords/model-search","display_name":"model search","score":0.5979999899864197},{"id":"https://openalex.org/keywords/disease-diagnosis","display_name":"disease diagnosis","score":0.6240000128746033}],"concepts":[{"id":"https://openalex.org/C2777553296","wikidata":"https://www.wikidata.org/wiki/Q201989","display_name":"Lyme disease","level":2,"score":0.9082236886024475},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.6691648960113525},{"id":"https://openalex.org/C158245278","wikidata":"https://www.wikidata.org/wiki/Q4386982","display_name":"Equidistant","level":2,"score":0.6009984016418457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.539749026298523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5114389657974243},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45122379064559937},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.3600584864616394},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.1281868815422058},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09234264492988586},{"id":"https://openalex.org/C203014093","wikidata":"https://www.wikidata.org/wiki/Q101929","display_name":"Immunology","level":1,"score":0.08900654315948486},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.145.4661","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.145.4661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.utia.cas.cz/files/mtr/pgm06/35_paper.pdf","raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:publications/09b748b0-9fe7-11db-8ed6-000ea68e967b","doi":null,"is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/09b748b0-9fe7-11db-8ed6-000ea68e967b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Olesen, K G, Hejlesen, O K, Dessau, R, Beltoft, I & Trangeled, M 2006, Diagnosing Lyme Disease : Tailoring patient specific Bayesian networks for temporal reasoning. in M Studeny & J Vomlel (eds), Proceedings of the Third European Workshop on Probabilistic Graphical Models (PGM \u201806. <Forlag uden navn>, pp. 231-238, European Workshop on Probabilistic Graphical Models, Prag, Czech Republic, 12/09/2006.","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"mag:5813897","doi":null,"is_oa":false,"landing_page_url":"https://www.utia.cas.cz/files/mtr/pgm06/35_paper.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306420740","display_name":"Probabilistic Graphical Models","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":"Probabilistic Graphical Models","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5683000087738037,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":4,"referenced_works":["https://openalex.org/W1543675445","https://openalex.org/W1608018123","https://openalex.org/W1755360231","https://openalex.org/W2763873423"],"related_works":["https://openalex.org/W1757668110","https://openalex.org/W2739353227","https://openalex.org/W2541080943","https://openalex.org/W7096944396","https://openalex.org/W3195400856","https://openalex.org/W2173494914","https://openalex.org/W2523450338","https://openalex.org/W2921838432","https://openalex.org/W2978643771","https://openalex.org/W7223146381"],"abstract_inverted_index":{"Lyme":[0,9],"disease":[1,10,29,62,97],"is":[2,11,31,98],"an":[3],"infection":[4],"evolving":[5],"in":[6,48],"three":[7],"stages.":[8],"characterised":[12],"by":[13,100],"a":[14,82,88,101],"number":[15],"of":[16,38,53,71,74,81,93,95,116],"symptoms":[17,55,75],"whose":[18],"manifestations":[19,118],"evolve":[20],"over":[21,76,119],"time.":[22,120],"In":[23],"order":[24],"to":[25,33],"correctly":[26],"classify":[27],"the":[28,35,39,51,58,61,66,72,79,96,106,111,114],"it":[30],"important":[32],"include":[34],"clinical":[36],"history":[37],"patient.":[40,67,90],"Consultations":[41],"are":[42],"typically":[43],"scattered":[44],"at":[45],"non-equidistant":[46],"points":[47],"time":[49,59,77,92],"and":[50],"probability":[52],"observing":[54],"depend":[56],"on":[57,65],"since":[60],"was":[63],"inflicted":[64],"A":[68],"simple":[69],"model":[70,85,102,109],"evolution":[73],"forms":[78],"basis":[80],"dynamically":[83],"tailored":[84],"that":[86,104],"describes":[87],"specific":[89],"The":[91],"infliction":[94],"estimated":[99],"search":[103],"identifies":[105],"most":[107],"probable":[108],"for":[110],"patient":[112],"given":[113],"pattern":[115],"symptom":[117],"1":[121]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-10-08T09:06:37.294493","created_date":"2016-06-24T00:00:00"}