{"id":"https://openalex.org/W3047340521","doi":"https://doi.org/10.1109/percomworkshops48775.2020.9156223","title":"Sepsis Prediction using Continuous and Categorical Features on Sporadic Data","display_name":"Sepsis Prediction using Continuous and Categorical Features on Sporadic Data","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3047340521","doi":"https://doi.org/10.1109/percomworkshops48775.2020.9156223","mag":"3047340521"},"language":"en","primary_location":{"id":"doi:10.1109/percomworkshops48775.2020.9156223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops48775.2020.9156223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5074514195","display_name":"Varsha Sharma","orcid":"https://orcid.org/0000-0002-6760-6416"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Varsha Sharma","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005227693","display_name":"Chirayata Bhattacharyya","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chirayata Bhattacharyya","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045058626","display_name":"Tanuka Bhattacharjee","orcid":null},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanuka Bhattacharjee","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018662978","display_name":"Sundeep Khandelwal","orcid":"https://orcid.org/0000-0001-5529-3187"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sundeep Khandelwal","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049873797","display_name":"Murali Poduval","orcid":"https://orcid.org/0000-0002-6821-0640"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Murali Poduval","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031860703","display_name":"Anirban Dutta Choudhury","orcid":"https://orcid.org/0000-0002-5005-8716"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anirban Dutta Choudhury","raw_affiliation_strings":["TCS Research & Innovation, India"],"affiliations":[{"raw_affiliation_string":"TCS Research & Innovation, India","institution_ids":["https://openalex.org/I55215948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5074514195"],"corresponding_institution_ids":["https://openalex.org/I55215948"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.08807945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9878000020980835,"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":0.9878000020980835,"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/T10218","display_name":"Sepsis Diagnosis and Treatment","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9775000214576721,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/categorical-variable","display_name":"Categorical variable","score":0.8553509712219238},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6317008137702942},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5601290464401245},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5506396889686584},{"id":"https://openalex.org/keywords/sliding-window-protocol","display_name":"Sliding window protocol","score":0.5278180241584778},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.5010867118835449},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5008172988891602},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.49903440475463867},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4838244318962097},{"id":"https://openalex.org/keywords/logit","display_name":"Logit","score":0.48249077796936035},{"id":"https://openalex.org/keywords/intensive-care","display_name":"Intensive care","score":0.4619920551776886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3791947364807129},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.37161821126937866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34858471155166626},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27234911918640137},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.2667974829673767},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.15558424592018127},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1521753966808319},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.10758611559867859},{"id":"https://openalex.org/keywords/intensive-care-medicine","display_name":"Intensive care medicine","score":0.08523562550544739}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8553509712219238},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6317008137702942},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5601290464401245},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5506396889686584},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.5278180241584778},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.5010867118835449},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5008172988891602},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.49903440475463867},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4838244318962097},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.48249077796936035},{"id":"https://openalex.org/C2987404301","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care","level":2,"score":0.4619920551776886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3791947364807129},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.37161821126937866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34858471155166626},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27234911918640137},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.2667974829673767},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15558424592018127},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1521753966808319},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.10758611559867859},{"id":"https://openalex.org/C177713679","wikidata":"https://www.wikidata.org/wiki/Q679690","display_name":"Intensive care medicine","level":1,"score":0.08523562550544739},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/percomworkshops48775.2020.9156223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/percomworkshops48775.2020.9156223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1898928487","https://openalex.org/W1977098485","https://openalex.org/W2007092752","https://openalex.org/W2125826936","https://openalex.org/W2128349740","https://openalex.org/W2131241448","https://openalex.org/W2154053567","https://openalex.org/W2280404143","https://openalex.org/W2282181907","https://openalex.org/W2332411917","https://openalex.org/W2396455095","https://openalex.org/W2735761750","https://openalex.org/W2801906473","https://openalex.org/W2995282027","https://openalex.org/W3046153892","https://openalex.org/W3162617641","https://openalex.org/W3183325496","https://openalex.org/W3200234412","https://openalex.org/W4247943214","https://openalex.org/W6678911119","https://openalex.org/W6771557539"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W4293192871","https://openalex.org/W3136973226","https://openalex.org/W4220968781","https://openalex.org/W2122407924"],"abstract_inverted_index":{"Sepsis":[0],"is":[1,26,51,144],"one":[2,17],"of":[3,8,18,41,73,131,150,156,168],"the":[4,19,71,78,100,113,120,148,151,157,162],"most":[5,20],"prevalent":[6],"causes":[7],"mortality":[9],"in":[10,30,116],"Intensive":[11],"Care":[12],"Units":[13],"(ICUs)":[14],"and":[15,32,56,65,134],"also":[16,103],"expensive":[21],"health-care":[22],"problems.":[23],"Delayed":[24],"treatment":[25],"associated":[27],"with":[28],"increase":[29],"death":[31],"financial":[33],"burden.":[34],"This":[35],"work":[36],"proposes":[37],"an":[38],"early":[39],"prediction":[40,79],"sepsis":[42],"validated":[43],"on":[44,91],"Physionet":[45],"Challenge":[46],"2019":[47],"dataset.":[48],"The":[49],"challenge":[50],"to":[52,83,94,108,118,146],"extract":[53],"continuous,":[54],"categorical":[55,110],"domain-specific":[57],"discriminating":[58],"features":[59,97,111],"from":[60,112,122],"highly":[61],"sporadic":[62,92],"lab":[63],"data":[64,76,93,115,163],"vital":[66],"signals.":[67],"We":[68,102],"find":[69],"that":[70,127],"imputation":[72],"extremely":[74],"isolated":[75],"lower":[77],"performance.":[80,139],"In":[81],"order":[82,117],"mitigate":[84],"this,":[85],"we":[86,125],"use":[87],"a":[88,105,128],"sliding":[89],"window":[90],"generate":[95,109],"continuous":[96],"which":[98],"capture":[99],"trend.":[101],"devise":[104],"binning":[106],"approach":[107],"aperiodic":[114],"discriminate":[119],"deviation":[121],"normalcy.":[123],"Lastly,":[124],"observe":[126],"logical":[129],"fusion":[130],"Random":[132],"Forest":[133],"Logit":[135],"Boost":[136],"provides":[137],"optimal":[138],"Normalized":[140],"Utility":[141],"Score":[142],"(NUS)":[143],"used":[145],"benchmark":[147],"performance":[149],"proposed":[152],"baselines.":[153],"Five-fold":[154],"cross-validation":[155],"best":[158],"preforming":[159],"pipeline":[160],"across":[161],"reveals":[164],"high":[165],"median":[166],"NUS":[167],"0.401.":[169]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
