{"id":"https://openalex.org/W4415871684","doi":"https://doi.org/10.3390/make7040136","title":"Explainable Deep Learning for Neonatal Jaundice Classification Using Uncalibrated Smartphone Images","display_name":"Explainable Deep Learning for Neonatal Jaundice Classification Using Uncalibrated Smartphone Images","publication_year":2025,"publication_date":"2025-11-04","ids":{"openalex":"https://openalex.org/W4415871684","doi":"https://doi.org/10.3390/make7040136"},"language":"en","primary_location":{"id":"doi:10.3390/make7040136","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040136","pdf_url":"https://www.mdpi.com/2504-4990/7/4/136/pdf?version=1762257856","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2504-4990/7/4/136/pdf?version=1762257856","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059077872","display_name":"Ashim Chakraborty","orcid":"https://orcid.org/0000-0002-1578-5539"},"institutions":[{"id":"https://openalex.org/I51216347","display_name":"Anglia Ruskin University","ror":"https://ror.org/0009t4v78","country_code":"GB","type":"education","lineage":["https://openalex.org/I51216347"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ashim Chakraborty","raw_affiliation_strings":["School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK","institution_ids":["https://openalex.org/I51216347"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120248955","display_name":"Yeshwanth Thota","orcid":null},"institutions":[{"id":"https://openalex.org/I51216347","display_name":"Anglia Ruskin University","ror":"https://ror.org/0009t4v78","country_code":"GB","type":"education","lineage":["https://openalex.org/I51216347"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yeshwanth Thota","raw_affiliation_strings":["School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK","institution_ids":["https://openalex.org/I51216347"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028548557","display_name":"Cristina Luca","orcid":null},"institutions":[{"id":"https://openalex.org/I51216347","display_name":"Anglia Ruskin University","ror":"https://ror.org/0009t4v78","country_code":"GB","type":"education","lineage":["https://openalex.org/I51216347"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Cristina Luca","raw_affiliation_strings":["School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK","institution_ids":["https://openalex.org/I51216347"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010222502","display_name":"Ian van der Linde","orcid":"https://orcid.org/0000-0002-8131-5906"},"institutions":[{"id":"https://openalex.org/I51216347","display_name":"Anglia Ruskin University","ror":"https://ror.org/0009t4v78","country_code":"GB","type":"education","lineage":["https://openalex.org/I51216347"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ian van der Linde","raw_affiliation_strings":["School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK","Vision and Eye Research Institute (VERI), School of Medicine, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK"],"affiliations":[{"raw_affiliation_string":"School of Computing and Information Science, Anglia Ruskin University, Cambridge CB1 1PT, UK","institution_ids":["https://openalex.org/I51216347"]},{"raw_affiliation_string":"Vision and Eye Research Institute (VERI), School of Medicine, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK","institution_ids":["https://openalex.org/I51216347"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010222502"],"corresponding_institution_ids":["https://openalex.org/I51216347"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4443411,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":"4","first_page":"136","last_page":"136"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12068","display_name":"Neonatal Health and Biochemistry","score":0.8047000169754028,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T12068","display_name":"Neonatal Health and Biochemistry","score":0.8047000169754028,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/T12460","display_name":"Pediatric Hepatobiliary Diseases and Treatments","score":0.019099999219179153,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.011099999770522118,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/preprocessor","display_name":"Preprocessor","score":0.7246999740600586},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7062000036239624},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.685699999332428},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6172999739646912},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5716000199317932},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.49630001187324524},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4823000133037567},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41940000653266907}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.842199981212616},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7246999740600586},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7062000036239624},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.685699999332428},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6172999739646912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5723999738693237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4823000133037567},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4309000074863434},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4016000032424927},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3644999861717224},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.357699990272522},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.35760000348091125},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3384000062942505},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.33489999175071716},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3271999955177307},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.3100000023841858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30090001225471497},{"id":"https://openalex.org/C2778456037","wikidata":"https://www.wikidata.org/wiki/Q133244","display_name":"Jaundice","level":2,"score":0.2957000136375427},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.2775000035762787},{"id":"https://openalex.org/C3019060180","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automated method","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/make7040136","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040136","pdf_url":"https://www.mdpi.com/2504-4990/7/4/136/pdf?version=1762257856","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8eb068d2b9fc4457aa4f0d34902f1ed8","is_oa":true,"landing_page_url":"https://doaj.org/article/8eb068d2b9fc4457aa4f0d34902f1ed8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Machine Learning and Knowledge Extraction, Vol 7, Iss 4, p 136 (2025)","raw_type":"article"},{"id":"pmh:oai:figshare.com:article/30847094","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":null,"raw_type":"Journal contribution"}],"best_oa_location":{"id":"doi:10.3390/make7040136","is_oa":true,"landing_page_url":"https://doi.org/10.3390/make7040136","pdf_url":"https://www.mdpi.com/2504-4990/7/4/136/pdf?version=1762257856","source":{"id":"https://openalex.org/S4210213891","display_name":"Machine Learning and Knowledge Extraction","issn_l":"2504-4990","issn":["2504-4990"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning and Knowledge Extraction","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311962","display_name":"Anglia Ruskin University","ror":"https://ror.org/0009t4v78"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4415871684.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2001412060","https://openalex.org/W2037340144","https://openalex.org/W2117506890","https://openalex.org/W2194775991","https://openalex.org/W2396249415","https://openalex.org/W2580260512","https://openalex.org/W2746042487","https://openalex.org/W2753051611","https://openalex.org/W2763945944","https://openalex.org/W2771408233","https://openalex.org/W2781921224","https://openalex.org/W2795312261","https://openalex.org/W2805962585","https://openalex.org/W2810712378","https://openalex.org/W2962858109","https://openalex.org/W2963150697","https://openalex.org/W3009384997","https://openalex.org/W3009862607","https://openalex.org/W3015156502","https://openalex.org/W3135678745","https://openalex.org/W3158664272","https://openalex.org/W3192595212","https://openalex.org/W3202183988","https://openalex.org/W3209742527","https://openalex.org/W4205538083","https://openalex.org/W4206834509","https://openalex.org/W4250928742","https://openalex.org/W4308458583","https://openalex.org/W4367175958","https://openalex.org/W4375955262","https://openalex.org/W4383368712","https://openalex.org/W4390874575","https://openalex.org/W4392015863","https://openalex.org/W4392162056","https://openalex.org/W4397009660","https://openalex.org/W4405013890","https://openalex.org/W4405276600","https://openalex.org/W4407722806","https://openalex.org/W4409174745","https://openalex.org/W4411956528"],"related_works":[],"abstract_inverted_index":{"Hyperbilirubinemia,":[0],"commonly":[1],"known":[2],"as":[3,31],"jaundice,":[4],"is":[5],"a":[6,41,55,104,144],"prevalent":[7],"condition":[8],"in":[9,15,63,116,120,168],"newborns,":[10],"primarily":[11],"arising":[12],"from":[13,93],"alterations":[14],"red":[16],"blood":[17],"cell":[18],"metabolism":[19],"during":[20],"the":[21,82,99,117,160,165],"first":[22],"week":[23],"of":[24,84,88,95,107,170],"life.":[25],"While":[26],"conventional":[27],"diagnostic":[28,48],"methods,":[29],"such":[30],"serum":[32],"analysis":[33],"and":[34,68,81,127,150,158],"transcutaneous":[35],"bilirubinometry,":[36],"are":[37,138],"effective,":[38],"there":[39],"remains":[40],"critical":[42],"need":[43],"for":[44,60],"robust,":[45],"non-invasive,":[46],"image-based":[47],"tools.":[49],"In":[50],"this":[51,111,121,130],"study,":[52],"we":[53,132],"propose":[54],"custom-designed":[56],"convolutional":[57],"neural":[58],"network":[59],"classifying":[61],"jaundice":[62],"neonatal":[64],"images.":[65],"Image":[66],"preprocessing":[67],"segmentation":[69],"techniques":[70],"were":[71],"systematically":[72],"evaluated.":[73],"The":[74],"optimal":[75],"workflow,":[76,146],"which":[77],"incorporated":[78],"contrast":[79],"enhancement":[80],"extraction":[83],"regular":[85],"skin":[86],"patches":[87],"144":[89,91],"\u00d7":[90],"pixels":[92],"regions":[94,162],"interest":[96],"segmented":[97],"using":[98],"Segment":[100],"Anything":[101],"Model,":[102],"achieved":[103],"testing":[105],"F1-score":[106],"0.80.":[108],"Beyond":[109],"performance,":[110],"study":[112],"addresses":[113],"numerous":[114],"shortcomings":[115],"existing":[118],"literature":[119],"area":[122],"relating":[123],"to":[124,141,156],"trust,":[125],"replicability,":[126],"transparency.":[128],"To":[129],"end,":[131],"employ":[133],"fair":[134],"performance":[135],"metrics":[136],"that":[137,163],"more":[139],"robust":[140],"class":[142],"imbalance,":[143],"transparent":[145],"share":[147],"source":[148],"code,":[149],"use":[151],"Gradient-weighted":[152],"Class":[153],"Activation":[154],"Mapping":[155],"visualise":[157],"quantify":[159],"image":[161],"influence":[164],"classifier\u2019s":[166],"predictions":[167],"pursuit":[169],"epistemic":[171],"justification.":[172]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-11-04T00:00:00"}
