{"id":"https://openalex.org/W3211490785","doi":"https://doi.org/10.3233/shti210800","title":"Encoding Health Records into Pathway Representations for Deep Learning","display_name":"Encoding Health Records into Pathway Representations for Deep Learning","publication_year":2021,"publication_date":"2021-11-18","ids":{"openalex":"https://openalex.org/W3211490785","doi":"https://doi.org/10.3233/shti210800","mag":"3211490785","pmid":"https://pubmed.ncbi.nlm.nih.gov/34795069"},"language":"en","primary_location":{"id":"doi:10.3233/shti210800","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti210800","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210800","source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210800","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Marco Luca Sbodio","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marco Luca Sbodio","raw_affiliation_strings":["IBM Research Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Natasha Mulligan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Natasha Mulligan","raw_affiliation_strings":["IBM Research Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Stefanie Speichert","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefanie Speichert","raw_affiliation_strings":["IBM Research Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Vanessa Lopez","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vanessa Lopez","raw_affiliation_strings":["IBM Research Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Joao Bettencourt-Silva","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Joao Bettencourt-Silva","raw_affiliation_strings":["IBM Research Europe"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM Research Europe","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7366,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.74267166,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"287","issue":null,"first_page":"8","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9779999852180481,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9779999852180481,"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/T10350","display_name":"Electronic Health Records Systems","score":0.0015999999595806003,"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/T10552","display_name":"Colorectal Cancer Screening and Detection","score":0.0010999999940395355,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/deep-learning","display_name":"Deep learning","score":0.8458999991416931},{"id":"https://openalex.org/keywords/health-records","display_name":"Health records","score":0.7324000000953674},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6685000061988831},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6362000107765198},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5392000079154968},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5321000218391418},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.3856000006198883}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.8458999991416931},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7784000039100647},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7724999785423279},{"id":"https://openalex.org/C3019952477","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Health records","level":3,"score":0.7324000000953674},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6685000061988831},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6362000107765198},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5392000079154968},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5321000218391418},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5101000070571899},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36649999022483826},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.3402000069618225},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.28839999437332153},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.27630001306533813},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.27160000801086426},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.2574000060558319}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016571","descriptor_name":"Neural Networks, Computer","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.3233/shti210800","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti210800","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210800","source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},{"id":"pmid:34795069","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34795069","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in health technology and informatics","raw_type":null}],"best_oa_location":{"id":"doi:10.3233/shti210800","is_oa":true,"landing_page_url":"https://doi.org/10.3233/shti210800","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI210800","source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3211490785.pdf","grobid_xml":"https://content.openalex.org/works/W3211490785.grobid-xml"},"referenced_works_count":3,"referenced_works":["https://openalex.org/W2404901863","https://openalex.org/W2625625371","https://openalex.org/W3141913663"],"related_works":[],"abstract_inverted_index":{"There":[0],"is":[1,91,135],"a":[2,16,20,30,45,61,74,88],"growing":[3],"trend":[4],"in":[5],"building":[6],"deep":[7,51],"learning":[8,25,52],"patient":[9,35],"representations":[10],"from":[11,37,64,132],"health":[12,38,67,133],"records":[13,39,68,134],"to":[14,33,41,72],"obtain":[15],"comprehensive":[17],"view":[18],"of":[19,84,116,119],"patient's":[21],"data":[22],"for":[23,50,109,129],"machine":[24],"tasks.":[26,53],"This":[27],"paper":[28],"proposes":[29],"reproducible":[31],"approach":[32],"generate":[34],"pathways":[36,63,131],"and":[40,69],"transform":[42],"them":[43,71],"into":[44],"machine-processable":[46],"image-like":[47],"structure":[48],"useful":[49],"Based":[54],"on":[55,87,99,123],"this":[56],"approach,":[57],"we":[58],"generated":[59],"over":[60],"million":[62],"FAIR":[65],"synthetic":[66],"used":[70],"train":[73],"convolutional":[75],"neural":[76],"network.":[77],"Our":[78],"initial":[79],"experiments":[80],"show":[81],"the":[82,85,100,114,117,120],"accuracy":[83],"CNN":[86],"prediction":[89],"task":[90],"comparable":[92],"or":[93],"better":[94],"than":[95],"other":[96],"autoencoders":[97,124],"trained":[98],"same":[101],"data,":[102],"while":[103],"requiring":[104],"significantly":[105],"less":[106],"computational":[107],"resources":[108],"training.":[110],"We":[111],"also":[112],"assess":[113],"impact":[115],"size":[118],"training":[121],"dataset":[122],"performances.":[125],"The":[126],"source":[127],"code":[128],"generating":[130],"provided":[136],"as":[137],"open":[138],"source.":[139]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2021-11-22T00:00:00"}
