{"id":"https://openalex.org/W4312080592","doi":"https://doi.org/10.1007/s10489-022-04327-0","title":"Rapid extraction of skin physiological parameters from hyperspectral images using machine learning","display_name":"Rapid extraction of skin physiological parameters from hyperspectral images using machine learning","publication_year":2022,"publication_date":"2022-12-10","ids":{"openalex":"https://openalex.org/W4312080592","doi":"https://doi.org/10.1007/s10489-022-04327-0"},"language":"en","primary_location":{"id":"doi:10.1007/s10489-022-04327-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-022-04327-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-022-04327-0.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Applied Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10489-022-04327-0.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051498528","display_name":"Teo Manojlovi\u0107","orcid":"https://orcid.org/0000-0002-8891-0935"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Teo Manojlovi\u0107","raw_affiliation_strings":["Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","Faculty of Engineering, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia"],"raw_orcid":"https://orcid.org/0000-0002-8891-0935","affiliations":[{"raw_affiliation_string":"Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","institution_ids":["https://openalex.org/I154347574"]},{"raw_affiliation_string":"Faculty of Engineering, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062914264","display_name":"Tadej Tomani\u010d","orcid":"https://orcid.org/0000-0002-5398-335X"},"institutions":[{"id":"https://openalex.org/I153976015","display_name":"University of Ljubljana","ror":"https://ror.org/05njb9z20","country_code":"SI","type":"education","lineage":["https://openalex.org/I153976015"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Tadej Tomani\u010d","raw_affiliation_strings":["Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, Ljubljana, 1000, Slovenia"],"raw_orcid":"https://orcid.org/0000-0002-5398-335X","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, Ljubljana, 1000, Slovenia","institution_ids":["https://openalex.org/I153976015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081398821","display_name":"Ivan \u0160tajduhar","orcid":"https://orcid.org/0000-0003-4758-7972"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":true,"raw_author_name":"Ivan \u0160tajduhar","raw_affiliation_strings":["Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","Faculty of Engineering, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia"],"raw_orcid":"https://orcid.org/0000-0003-4758-7972","affiliations":[{"raw_affiliation_string":"Center for Artificial Intelligence and Cybersecurity, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","institution_ids":["https://openalex.org/I154347574"]},{"raw_affiliation_string":"Faculty of Engineering, University of Rijeka, Vukovarska ulica 58, Rijeka, 51000, Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011044778","display_name":"Matija Milani\u010d","orcid":"https://orcid.org/0000-0002-4417-0293"},"institutions":[{"id":"https://openalex.org/I153976015","display_name":"University of Ljubljana","ror":"https://ror.org/05njb9z20","country_code":"SI","type":"education","lineage":["https://openalex.org/I153976015"]},{"id":"https://openalex.org/I3006985408","display_name":"Jo\u017eef Stefan Institute","ror":"https://ror.org/05060sz93","country_code":"SI","type":"facility","lineage":["https://openalex.org/I3006985408"]}],"countries":["SI"],"is_corresponding":false,"raw_author_name":"Matija Milani\u010d","raw_affiliation_strings":["Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, Ljubljana, 1000, Slovenia","Jozef Stefan Institute, University of Ljubljana, Jamova cesta 39, Ljubljana, 1000, Slovenia"],"raw_orcid":"https://orcid.org/0000-0002-4417-0293","affiliations":[{"raw_affiliation_string":"Faculty of Mathematics and Physics, University of Ljubljana, Jadranska ulica 19, Ljubljana, 1000, Slovenia","institution_ids":["https://openalex.org/I153976015"]},{"raw_affiliation_string":"Jozef Stefan Institute, University of Ljubljana, Jamova cesta 39, Ljubljana, 1000, Slovenia","institution_ids":["https://openalex.org/I3006985408"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5081398821"],"corresponding_institution_ids":["https://openalex.org/I154347574"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":1.4324,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80849487,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"53","issue":"13","first_page":"16519","last_page":"16539"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9993000030517578,"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/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.9993000030517578,"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/T11013","display_name":"Skin Protection and Aging","score":0.9854999780654907,"subfield":{"id":"https://openalex.org/subfields/2708","display_name":"Dermatology"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7266597747802734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7257057428359985},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.637111485004425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5391530990600586},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.5146923661231995},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4962511658668518},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.448402464389801},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.44823190569877625},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4413367509841919},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.42844194173812866},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4119921922683716},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4040793180465698},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3780639171600342},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19948232173919678},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.173348069190979}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7266597747802734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7257057428359985},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.637111485004425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5391530990600586},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.5146923661231995},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4962511658668518},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.448402464389801},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.44823190569877625},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4413367509841919},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.42844194173812866},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4119921922683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4040793180465698},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3780639171600342},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19948232173919678},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.173348069190979},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10489-022-04327-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-022-04327-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-022-04327-0.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Applied Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10489-022-04327-0","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10489-022-04327-0","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10489-022-04327-0.pdf","source":{"id":"https://openalex.org/S74726891","display_name":"Applied Intelligence","issn_l":"0924-669X","issn":["0924-669X","1573-7497"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","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":"Applied Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6000000238418579,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G14806187","display_name":"Medical Physics","funder_award_id":"P1-0389","funder_id":"https://openalex.org/F4320322554","funder_display_name":"Javna Agencija za Raziskovalno Dejavnost RS"},{"id":"https://openalex.org/G1941838634","display_name":null,"funder_award_id":"grant number IP-2020-02-3770","funder_id":"https://openalex.org/F4320322674","funder_display_name":"Hrvatska Zaklada za Znanost"},{"id":"https://openalex.org/G2143379086","display_name":"Machine Learning for Knowledge Transfer in Medical Radiology","funder_award_id":"IP-2020-02-3770","funder_id":"https://openalex.org/F4320322674","funder_display_name":"Hrvatska Zaklada za Znanost"},{"id":"https://openalex.org/G2997764149","display_name":null,"funder_award_id":"UNIRI-TEHNIC-18-15","funder_id":"https://openalex.org/F1002590718","funder_display_name":"Sveu\u010dili\u0161te u Rijeci"},{"id":"https://openalex.org/G6462038999","display_name":null,"funder_award_id":"IP-2020-02","funder_id":"https://openalex.org/F4320322674","funder_display_name":"Hrvatska Zaklada za Znanost"},{"id":"https://openalex.org/G6876463463","display_name":"Vascularization and vascular effects as predictive factors for local ablative techniques","funder_award_id":"J3-3083","funder_id":"https://openalex.org/F4320322554","funder_display_name":"Javna Agencija za Raziskovalno Dejavnost RS"}],"funders":[{"id":"https://openalex.org/F1002590718","display_name":"Sveu\u010dili\u0161te u Rijeci","ror":"https://ror.org/05r8dqr10"},{"id":"https://openalex.org/F4320322554","display_name":"Javna Agencija za Raziskovalno Dejavnost RS","ror":"https://ror.org/059bp8k51"},{"id":"https://openalex.org/F4320322674","display_name":"Hrvatska Zaklada za Znanost","ror":"https://ror.org/03n51vw80"},{"id":"https://openalex.org/F4320324592","display_name":"Univerza v Ljubljani","ror":"https://ror.org/05njb9z20"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312080592.pdf","grobid_xml":"https://content.openalex.org/works/W4312080592.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1969657538","https://openalex.org/W1987971958","https://openalex.org/W1988386267","https://openalex.org/W1989724844","https://openalex.org/W1989992429","https://openalex.org/W2002540981","https://openalex.org/W2010319424","https://openalex.org/W2013492930","https://openalex.org/W2064564194","https://openalex.org/W2097683070","https://openalex.org/W2107003353","https://openalex.org/W2111761460","https://openalex.org/W2121337633","https://openalex.org/W2123477094","https://openalex.org/W2123517881","https://openalex.org/W2143150256","https://openalex.org/W2295208326","https://openalex.org/W2608595004","https://openalex.org/W2682360066","https://openalex.org/W2791006446","https://openalex.org/W2792341186","https://openalex.org/W2904784562","https://openalex.org/W2911524083","https://openalex.org/W2911964244","https://openalex.org/W2917353878","https://openalex.org/W2950243097","https://openalex.org/W2983043578","https://openalex.org/W3012135036","https://openalex.org/W3014740345","https://openalex.org/W3036583555","https://openalex.org/W3087334746","https://openalex.org/W3095065295","https://openalex.org/W3119311349","https://openalex.org/W3139265876","https://openalex.org/W4211227021","https://openalex.org/W4220984912","https://openalex.org/W4226188683","https://openalex.org/W4229014074","https://openalex.org/W4235325762"],"related_works":["https://openalex.org/W4321636153","https://openalex.org/W2051197289","https://openalex.org/W3208266890","https://openalex.org/W2996933976","https://openalex.org/W4377964522","https://openalex.org/W3173596272","https://openalex.org/W2781623059","https://openalex.org/W2985924212","https://openalex.org/W2345184372","https://openalex.org/W3195168932"],"abstract_inverted_index":{"Abstract":[0],"Noninvasive":[1],"assessment":[2],"of":[3,22,41,66,139,154,159,250],"skin":[4,110,191,252],"structure":[5],"using":[6,42,120,150,169],"hyperspectral":[7],"images":[8],"has":[9,35],"been":[10,36],"intensively":[11],"studied":[12],"in":[13,222,255],"recent":[14],"years.":[15],"Due":[16],"to":[17,47,58,76,107,230],"the":[18,23,28,39,49,60,63,67,77,121,137,160,177,185,197,203,209,214,218],"high":[19],"computational":[20],"cost":[21],"classical":[24],"methods,":[25],"such":[26],"as":[27],"inverse":[29,80],"Monte":[30],"Carlo":[31],"(IMC),":[32],"much":[33],"research":[34],"done":[37],"with":[38,193],"aim":[40],"machine":[43],"learning":[44],"(ML)":[45],"methods":[46,69],"reduce":[48],"time":[50,229],"required":[51],"for":[52,70,233],"estimating":[53],"parameters.":[54,111],"This":[55],"study":[56],"aims":[57],"evaluate":[59],"accuracy":[61],"and":[62,73,100,163,189],"estimation":[64],"speed":[65],"ML":[68,244],"this":[71],"purpose":[72],"compare":[74],"them":[75],"traditionally":[78],"used":[79],"adding-doubling":[81,122],"(IAD)":[82],"algorithm.":[83,123,199],"We":[84],"trained":[85,115,143,148,168],"three":[86,141],"models":[87,113,165],"\u2013":[88,106],"an":[89],"artificial":[90],"neural":[91,97],"network":[92,98],"(ANN),":[93],"a":[94,101,130,152,234],"1D":[95],"convolutional":[96],"(CNN),":[99],"random":[102],"forests":[103],"(RF)":[104],"model":[105,135,146,211,216],"predict":[108],"seven":[109],"The":[112,227],"were":[114,167,173],"on":[116,157,176,221],"simulated":[117,170,201],"data":[118],"computed":[119],"To":[124],"improve":[125],"predictive":[126],"performance,":[127],"we":[128],"introduced":[129],"stacked":[131],"dynamic":[132],"weighting":[133],"(SDW)":[134],"combining":[136],"predictions":[138],"all":[140],"individually":[142],"models.":[144],"SDW":[145,215],"was":[147,206,237],"by":[149,196,208],"only":[151],"handful":[153],"real-world":[155],"spectra":[156,192,194,225],"top":[158],"ANN,":[161],"CNN":[162],"RF":[164,210],"that":[166,243],"data.":[171],"Models":[172],"evaluated":[174],"based":[175],"estimated":[178],"parameters\u2019":[179],"mean":[180],"absolute":[181],"error":[182],"(MAE),":[183],"considering":[184],"surface":[186],"inclination":[187],"angle":[188],"comparing":[190],"fitted":[195],"IAD":[198],"On":[200],"data,":[202],"lowest":[204,219],"MAE":[205,220],"achieved":[207,217],"(0.0030),":[212],"while":[213],"vivo":[223],"measured":[224],"(0.0113).":[226],"shortest":[228],"estimate":[231],"parameters":[232,254],"single":[235],"spectrum":[236],"93.05":[238],"\u03bc":[239],"s.":[240],"Results":[241],"suggest":[242],"algorithms":[245],"can":[246],"produce":[247],"accurate":[248],"estimates":[249],"human":[251],"optical":[253],"near":[256],"real-time.":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
