{"id":"https://openalex.org/W4406458727","doi":"https://doi.org/10.1109/bigdata62323.2024.10825661","title":"Improving Medical Imaging Model Calibration through Probabilistic Embedding","display_name":"Improving Medical Imaging Model Calibration through Probabilistic Embedding","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458727","doi":"https://doi.org/10.1109/bigdata62323.2024.10825661"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5103106209","display_name":"B. Han","orcid":"https://orcid.org/0009-0007-5986-0266"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bonian Han","raw_affiliation_strings":["Hangzhou Dianzi University,Department of Statistics,China"],"affiliations":[{"raw_affiliation_string":"Hangzhou Dianzi University,Department of Statistics,China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115924983","display_name":"Yuktha Priya Masupalli","orcid":null},"institutions":[{"id":"https://openalex.org/I1335518801","display_name":"Texas A&M University \u2013 San Antonio","ror":"https://ror.org/0084njv03","country_code":"US","type":"education","lineage":["https://openalex.org/I1335518801"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuktha Priya Masupalli","raw_affiliation_strings":["Texas A&#x0026;M University,Department of Computational, Engineering, and Mathematical Sciences,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"Texas A&#x0026;M University,Department of Computational, Engineering, and Mathematical Sciences,San Antonio,USA","institution_ids":["https://openalex.org/I1335518801"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078449028","display_name":"Xin Xing","orcid":"https://orcid.org/0000-0001-7207-5149"},"institutions":[{"id":"https://openalex.org/I1335518801","display_name":"Texas A&M University \u2013 San Antonio","ror":"https://ror.org/0084njv03","country_code":"US","type":"education","lineage":["https://openalex.org/I1335518801"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Xing","raw_affiliation_strings":["Texas A&#x0026;M University,Department of Computational, Engineering, and Mathematical Sciences,San Antonio,USA"],"affiliations":[{"raw_affiliation_string":"Texas A&#x0026;M University,Department of Computational, Engineering, and Mathematical Sciences,San Antonio,USA","institution_ids":["https://openalex.org/I1335518801"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070521525","display_name":"Gongbo Liang","orcid":"https://orcid.org/0000-0002-6700-6664"},"institutions":[{"id":"https://openalex.org/I122266389","display_name":"University of Nebraska at Omaha","ror":"https://ror.org/04yrkc140","country_code":"US","type":"education","lineage":["https://openalex.org/I122266389"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gongbo Liang","raw_affiliation_strings":["University of Nebraska Omaha,College of Information Science &#x0026; Technology,USA"],"affiliations":[{"raw_affiliation_string":"University of Nebraska Omaha,College of Information Science &#x0026; Technology,USA","institution_ids":["https://openalex.org/I122266389"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103106209"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.43324381,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4490","last_page":"4496"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/T11361","display_name":"Digital Radiography and Breast Imaging","score":0.9876999855041504,"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"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/calibration","display_name":"Calibration","score":0.7120722532272339},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.710623025894165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6270560026168823},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6191744804382324},{"id":"https://openalex.org/keywords/medical-imaging","display_name":"Medical imaging","score":0.5409442186355591},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4695582687854767},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.3345728814601898},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.17046579718589783},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12745341658592224},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12324443459510803}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7120722532272339},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.710623025894165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6270560026168823},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6191744804382324},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.5409442186355591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4695582687854767},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3345728814601898},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.17046579718589783},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12745341658592224},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12324443459510803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1821462560","https://openalex.org/W1901129140","https://openalex.org/W2101771332","https://openalex.org/W2108598243","https://openalex.org/W2137556846","https://openalex.org/W2141619730","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2254249950","https://openalex.org/W2435090885","https://openalex.org/W2560662850","https://openalex.org/W2798251715","https://openalex.org/W2804697534","https://openalex.org/W2959687571","https://openalex.org/W2964324313","https://openalex.org/W2970121940","https://openalex.org/W2971118045","https://openalex.org/W2990625787","https://openalex.org/W3004463834","https://openalex.org/W3080137426","https://openalex.org/W3160329607","https://openalex.org/W3163674776","https://openalex.org/W4200181029","https://openalex.org/W4224133960","https://openalex.org/W4297798436","https://openalex.org/W4306706453","https://openalex.org/W4309185522","https://openalex.org/W4312398513","https://openalex.org/W4366774505","https://openalex.org/W4385420376","https://openalex.org/W4388520228","https://openalex.org/W4395702004","https://openalex.org/W6638523607","https://openalex.org/W6732696085","https://openalex.org/W6739651123","https://openalex.org/W6745136726","https://openalex.org/W6751754606","https://openalex.org/W6766763711","https://openalex.org/W6767220907","https://openalex.org/W6783449658","https://openalex.org/W6846226315"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2345479200","https://openalex.org/W2050807133","https://openalex.org/W1985504019","https://openalex.org/W3086104399","https://openalex.org/W328486336","https://openalex.org/W1995688399","https://openalex.org/W2042967125","https://openalex.org/W2443196326"],"abstract_inverted_index":{"Neural":[0],"network":[1],"model":[2],"calibration":[3,19,98],"is":[4],"crucial":[5],"in":[6,94],"medical":[7,82],"imaging,":[8],"where":[9],"accurate":[10],"probabilistic":[11,48,64],"predictions":[12,61],"are":[13],"essential":[14],"for":[15],"informed":[16],"decision-making.":[17],"Existing":[18],"techniques":[20,93],"often":[21],"introduce":[22],"additional":[23],"complexity":[24],"and":[25,99],"may":[26],"not":[27],"fully":[28],"capture":[29],"the":[30,35,59,66,75],"inherent":[31],"uncertainty":[32,52,71],"associated":[33],"with":[34],"tasks.":[36,84],"To":[37],"address":[38],"these":[39],"challenges,":[40],"we":[41],"propose":[42],"a":[43,54,63],"novel":[44],"approach":[45,79],"based":[46],"on":[47,80],"embedding":[49,58],"that":[50],"models":[51],"through":[53],"Gaussian":[55],"distribution.":[56],"By":[57],"model\u2019s":[60],"into":[62],"space,":[65],"proposed":[67],"method":[68,90],"enables":[69],"effective":[70],"quantification.":[72],"We":[73],"demonstrate":[74],"effectiveness":[76],"of":[77,96],"our":[78,89],"multiple":[81],"imaging":[83],"The":[85],"experimental":[86],"result":[87],"shows":[88],"outperforms":[91],"existing":[92],"terms":[95],"both":[97],"accuracy.":[100]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
