{"id":"https://openalex.org/W4288068807","doi":"https://doi.org/10.1038/s41746-022-00649-y","title":"Machine learning for real-time aggregated prediction of hospital admission for emergency patients","display_name":"Machine learning for real-time aggregated prediction of hospital admission for emergency patients","publication_year":2022,"publication_date":"2022-07-26","ids":{"openalex":"https://openalex.org/W4288068807","doi":"https://doi.org/10.1038/s41746-022-00649-y","pmid":"https://pubmed.ncbi.nlm.nih.gov/35882903"},"language":"en","primary_location":{"id":"doi:10.1038/s41746-022-00649-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41746-022-00649-y","pdf_url":"https://www.nature.com/articles/s41746-022-00649-y.pdf","source":{"id":"https://openalex.org/S4210195431","display_name":"npj Digital Medicine","issn_l":"2398-6352","issn":["2398-6352"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"npj Digital Medicine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.nature.com/articles/s41746-022-00649-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007465189","display_name":"Zella King","orcid":"https://orcid.org/0000-0001-7389-1527"},"institutions":[{"id":"https://openalex.org/I164213776","display_name":"King's College - North Carolina","ror":"https://ror.org/022f44628","country_code":"US","type":"education","lineage":["https://openalex.org/I164213776"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB","US"],"is_corresponding":true,"raw_author_name":"Zella King","raw_affiliation_strings":["Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK. zella.king@ucl.ac.uk","Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK. zella.king@ucl.ac.uk","Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK. zella.king@ucl.ac.uk","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK. zella.king@ucl.ac.uk","institution_ids":["https://openalex.org/I164213776","https://openalex.org/I45129253"]},{"raw_affiliation_string":"Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010087284","display_name":"Joseph Farrington","orcid":"https://orcid.org/0000-0003-4156-3419"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Joseph Farrington","raw_affiliation_strings":["Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK"],"raw_orcid":"https://orcid.org/0000-0003-4156-3419","affiliations":[{"raw_affiliation_string":"Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000912579","display_name":"Martin Utley","orcid":"https://orcid.org/0000-0001-9928-1516"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Martin Utley","raw_affiliation_strings":["Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022988243","display_name":"Enoch Kung","orcid":"https://orcid.org/0000-0001-7174-8057"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Enoch Kung","raw_affiliation_strings":["Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011558684","display_name":"Samer Elkhodair","orcid":null},"institutions":[{"id":"https://openalex.org/I1340918713","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1340918713"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Samer Elkhodair","raw_affiliation_strings":["University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK","institution_ids":["https://openalex.org/I1340918713","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068199165","display_name":"Steve Harris","orcid":"https://orcid.org/0000-0002-4982-1374"},"institutions":[{"id":"https://openalex.org/I1340918713","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1340918713"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Steve Harris","raw_affiliation_strings":["University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK","institution_ids":["https://openalex.org/I1340918713","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039997912","display_name":"Richard Sekula","orcid":null},"institutions":[{"id":"https://openalex.org/I1340918713","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1340918713"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Richard Sekula","raw_affiliation_strings":["University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK","institution_ids":["https://openalex.org/I1340918713","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067786018","display_name":"Jonathan Gillham","orcid":"https://orcid.org/0009-0007-4110-7284"},"institutions":[{"id":"https://openalex.org/I1340918713","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I1340918713"]},{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jonathan Gillham","raw_affiliation_strings":["University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University College London Hospitals NHS Foundation Trust, 250 Euston Road, London, NW1 2PG, UK","institution_ids":["https://openalex.org/I1340918713","https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101786299","display_name":"Kezhi Li","orcid":"https://orcid.org/0000-0003-3073-3128"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Kezhi Li","raw_affiliation_strings":["Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK"],"raw_orcid":"https://orcid.org/0000-0003-3073-3128","affiliations":[{"raw_affiliation_string":"Institute of Health Informatics, University College London, 222 Euston Road, London, NW1 2DA, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031138978","display_name":"Sonya Crowe","orcid":"https://orcid.org/0000-0003-1882-5476"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sonya Crowe","raw_affiliation_strings":["Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK"],"raw_orcid":"https://orcid.org/0000-0003-1882-5476","affiliations":[{"raw_affiliation_string":"Clinical Operational Research Unit, University College London, 4 Taviton Street, London, WC1H 0BT, UK","institution_ids":["https://openalex.org/I45129253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007465189"],"corresponding_institution_ids":["https://openalex.org/I164213776","https://openalex.org/I45129253"],"apc_list":{"value":3060,"currency":"USD","value_usd":3060},"apc_paid":{"value":3060,"currency":"USD","value_usd":3060},"fwci":16.7259,"has_fulltext":true,"cited_by_count":73,"citation_normalized_percentile":{"value":0.99608813,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"5","issue":"1","first_page":"104","last_page":"104"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11095","display_name":"Emergency and Acute Care Studies","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"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/T11095","display_name":"Emergency and Acute Care Studies","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/2711","display_name":"Emergency Medicine"},"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9959999918937683,"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":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/emergency-department","display_name":"Emergency department","score":0.7639546394348145},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5486956834793091},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.5355322957038879},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.5059952139854431},{"id":"https://openalex.org/keywords/emergency-medicine","display_name":"Emergency medicine","score":0.48859888315200806},{"id":"https://openalex.org/keywords/electronic-health-record","display_name":"Electronic health record","score":0.4690221846103668},{"id":"https://openalex.org/keywords/triage","display_name":"Triage","score":0.44663307070732117},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.43567782640457153},{"id":"https://openalex.org/keywords/zip-code","display_name":"Zip code","score":0.4305627942085266},{"id":"https://openalex.org/keywords/medical-emergency","display_name":"Medical emergency","score":0.42115071415901184},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41827359795570374},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4158094525337219},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4146113395690918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3357178568840027},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.21946460008621216},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14935648441314697},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.14503690600395203}],"concepts":[{"id":"https://openalex.org/C2780724011","wikidata":"https://www.wikidata.org/wiki/Q1295316","display_name":"Emergency department","level":2,"score":0.7639546394348145},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5486956834793091},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5355322957038879},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.5059952139854431},{"id":"https://openalex.org/C194828623","wikidata":"https://www.wikidata.org/wiki/Q2861470","display_name":"Emergency medicine","level":1,"score":0.48859888315200806},{"id":"https://openalex.org/C3020144179","wikidata":"https://www.wikidata.org/wiki/Q10871684","display_name":"Electronic health record","level":3,"score":0.4690221846103668},{"id":"https://openalex.org/C2777120189","wikidata":"https://www.wikidata.org/wiki/Q780067","display_name":"Triage","level":2,"score":0.44663307070732117},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.43567782640457153},{"id":"https://openalex.org/C3018590553","wikidata":"https://www.wikidata.org/wiki/Q136208","display_name":"Zip code","level":2,"score":0.4305627942085266},{"id":"https://openalex.org/C545542383","wikidata":"https://www.wikidata.org/wiki/Q2751242","display_name":"Medical emergency","level":1,"score":0.42115071415901184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41827359795570374},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4158094525337219},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4146113395690918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3357178568840027},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.21946460008621216},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14935648441314697},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.14503690600395203},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","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/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1038/s41746-022-00649-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41746-022-00649-y","pdf_url":"https://www.nature.com/articles/s41746-022-00649-y.pdf","source":{"id":"https://openalex.org/S4210195431","display_name":"npj Digital Medicine","issn_l":"2398-6352","issn":["2398-6352"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"npj Digital Medicine","raw_type":"journal-article"},{"id":"pmid:35882903","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35882903","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":"NPJ digital medicine","raw_type":null},{"id":"pmh:oai:doaj.org/article:001d623296ef42d78609d2153482f171","is_oa":true,"landing_page_url":"https://doaj.org/article/001d623296ef42d78609d2153482f171","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"npj Digital Medicine, Vol 5, Iss 1, Pp 1-12 (2022)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:9321296","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9321296","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"NPJ Digit Med","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1038/s41746-022-00649-y","is_oa":true,"landing_page_url":"https://doi.org/10.1038/s41746-022-00649-y","pdf_url":"https://www.nature.com/articles/s41746-022-00649-y.pdf","source":{"id":"https://openalex.org/S4210195431","display_name":"npj Digital Medicine","issn_l":"2398-6352","issn":["2398-6352"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319908","host_organization_name":"Nature Portfolio","host_organization_lineage":["https://openalex.org/P4310319908","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Nature Portfolio","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"npj Digital Medicine","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.7799999713897705}],"awards":[{"id":"https://openalex.org/G149564501","display_name":"Digitally adapted, hyper-local realtime bed forecasting to manage flow for NHS wards","funder_award_id":"AI_AWARD01786","funder_id":"https://openalex.org/F4320319990","funder_display_name":"National Institute for Health and Care Research"},{"id":"https://openalex.org/G1685843087","display_name":"Institutional Strategic Support Fund","funder_award_id":"204841","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"},{"id":"https://openalex.org/G6709183389","display_name":null,"funder_award_id":"204841/Z/16/Z","funder_id":"https://openalex.org/F4320311904","funder_display_name":"Wellcome Trust"}],"funders":[{"id":"https://openalex.org/F4320311904","display_name":"Wellcome Trust","ror":"https://ror.org/029chgv08"},{"id":"https://openalex.org/F4320318751","display_name":"International Seafood Sustainability Foundation","ror":null},{"id":"https://openalex.org/F4320319990","display_name":"National Institute for Health and Care Research","ror":"https://ror.org/0187kwz08"},{"id":"https://openalex.org/F4320319994","display_name":"Department of Health and Social Care","ror":"https://ror.org/03sbpja79"},{"id":"https://openalex.org/F4320325311","display_name":"University College London Hospitals NHS Foundation Trust","ror":"https://ror.org/042fqyp44"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1593354804","https://openalex.org/W1608285042","https://openalex.org/W1887152358","https://openalex.org/W1970514818","https://openalex.org/W1995635991","https://openalex.org/W2019781618","https://openalex.org/W2037810045","https://openalex.org/W2047452988","https://openalex.org/W2063107541","https://openalex.org/W2078242043","https://openalex.org/W2082762510","https://openalex.org/W2097360283","https://openalex.org/W2146767951","https://openalex.org/W2295598076","https://openalex.org/W2567296875","https://openalex.org/W2587730730","https://openalex.org/W2614103315","https://openalex.org/W2748232622","https://openalex.org/W2755742863","https://openalex.org/W2788608859","https://openalex.org/W2797650827","https://openalex.org/W2884597820","https://openalex.org/W2892592994","https://openalex.org/W2895763047","https://openalex.org/W2929110666","https://openalex.org/W2960661706","https://openalex.org/W2965485927","https://openalex.org/W2984135870","https://openalex.org/W2994958466","https://openalex.org/W2996717911","https://openalex.org/W2999209042","https://openalex.org/W3009583110","https://openalex.org/W3013578857","https://openalex.org/W3024047754","https://openalex.org/W3028279553","https://openalex.org/W3081126843","https://openalex.org/W3172740468","https://openalex.org/W3200896515","https://openalex.org/W3214405491","https://openalex.org/W4200271217","https://openalex.org/W4294541781","https://openalex.org/W6772379445"],"related_works":["https://openalex.org/W1975091423","https://openalex.org/W2033023095","https://openalex.org/W2144451503","https://openalex.org/W125325933","https://openalex.org/W2051773733","https://openalex.org/W2941176721","https://openalex.org/W3015660457","https://openalex.org/W2909333182","https://openalex.org/W1983600708","https://openalex.org/W3149293204"],"abstract_inverted_index":{"Machine":[0],"learning":[1],"for":[2,17,107,146],"hospital":[3],"operations":[4],"is":[5],"under-studied.":[6],"We":[7,135],"present":[8],"a":[9,20,91,108,131],"prediction":[10],"pipeline":[11,89],"that":[12],"uses":[13],"live":[14],"electronic":[15],"health-records":[16],"patients":[18,75,78],"in":[19],"UK":[21],"teaching":[22],"hospital's":[23],"emergency":[24,33,83],"department":[25],"(ED)":[26],"to":[27,41,49,66,80],"generate":[28],"short-term,":[29],"probabilistic":[30],"forecasts":[31],"of":[32,37,58,62,70,96,102,123,127,141],"admissions.":[34],"A":[35],"set":[36],"XGBoost":[38],"classifiers":[39],"applied":[40],"109,465":[42],"ED":[43,74],"visits":[44,116],"yielded":[45],"AUROCs":[46,122],"from":[47],"0.82":[48],"0.90":[50],"depending":[51],"on":[52],"elapsed":[53],"visit-time":[54],"at":[55],"the":[56,68,118],"point":[57],"prediction.":[59],"Patient-level":[60],"probabilities":[61],"admission":[63],"were":[64],"aggregated":[65],"forecast":[67],"number":[69],"admissions":[71,84,98],"among":[72],"current":[73],"and,":[76],"incorporating":[77],"yet":[79],"arrive,":[81],"total":[82],"within":[85],"specified":[86],"time-windows.":[87],"The":[88],"gave":[90,121],"mean":[92],"absolute":[93],"error":[94,101],"(MAE)":[95],"4.0":[97],"(mean":[99],"percentage":[100],"17%)":[103],"versus":[104,130],"6.5":[105],"(32%)":[106],"benchmark":[109],"metric.":[110],"Models":[111],"developed":[112],"with":[113],"104,504":[114],"later":[115],"during":[117],"Covid-19":[119],"pandemic":[120],"0.68-0.90":[124],"and":[125,143,154],"MAE":[126],"4.2":[128],"(30%)":[129],"4.9":[132],"(33%)":[133],"benchmark.":[134],"discuss":[136],"how":[137],"we":[138],"surmounted":[139],"challenges":[140],"designing":[142],"implementing":[144],"models":[145],"real-time":[147],"use,":[148],"including":[149],"temporal":[150],"framing,":[151],"data":[152],"preparation,":[153],"changing":[155],"operational":[156],"conditions.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":14},{"year":2025,"cited_by_count":26},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":14},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}