{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T14:06:52Z","timestamp":1789567612740,"version":"build-2803163510"},"reference-count":53,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100001831","name":"Lynn Sage Breast Cancer Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001831","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U24NS133949"],"award-info":[{"award-number":["U24NS133949"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["UL1TR001422"],"award-info":[{"award-number":["UL1TR001422"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01LM013523"],"award-info":[{"award-number":["R01LM013523"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01CA220401"],"award-info":[{"award-number":["U01CA220401"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01HD116699"],"award-info":[{"award-number":["R01HD116699"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01EB030130"],"award-info":[{"award-number":["R01EB030130"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Placenta"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.placenta.2026.05.028","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T16:12:52Z","timestamp":1779466372000},"page":"204-210","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Machine learning identification of maternal inflammatory response and systemic inflammatory response from placental membrane whole slide images"],"prefix":"10.1016","volume":"181","author":[{"given":"Abhishek","family":"Sharma","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramin","family":"Nateghi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marina","family":"Ayad","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lee A.D.","family":"Cooper","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4086-057X","authenticated-orcid":false,"given":"Jeffery A.","family":"Goldstein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.placenta.2026.05.028_bib1","first-page":"8090","article-title":"Clinical chorioamnionitis and histologic placental inflammation: association with early-neonatal sepsis","volume":"35","author":"Rallis","year":"2022","journal-title":"J. Matern.-Fetal Neonatal Med. Off. J. Eur. Assoc. Perinat. Med. Fed. Asia Ocean. Perinat. Soc. Int. Soc. Perinat. Obstet."},{"key":"10.1016\/j.placenta.2026.05.028_bib2","first-page":"364","article-title":"Histological chorioamnionitis - implication for bacterial colonization, laboratory markers of infection, and early onset sepsis in very-low-birth-weight neonates","volume":"25","author":"Lee","year":"2012","journal-title":"J. Matern.-Fetal Neonatal Med. Off. J. Eur. Assoc. Perinat. Med. Fed. Asia Ocean. Perinat. Soc. Int. Soc. Perinat. Obstet."},{"key":"10.1016\/j.placenta.2026.05.028_bib3","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0031819","article-title":"Acute histologic chorioamnionitis at term: nearly always noninfectious","volume":"7","author":"Roberts","year":"2012","journal-title":"PLoS One"},{"key":"10.1016\/j.placenta.2026.05.028_bib4","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1210\/en.2011-1506","article-title":"Stretch and inflammatory cytokines drive myometrial chemokine expression via NF-\u03baB activation","volume":"153","author":"Hua","year":"2012","journal-title":"Endocrinology"},{"key":"10.1016\/j.placenta.2026.05.028_bib5","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1111\/aji.12296","article-title":"Prevalence and clinical significance of sterile intra-amniotic inflammation in patients with preterm labor and intact membranes","volume":"72","author":"Romero","year":"2014","journal-title":"Am. J. Reprod. Immunol."},{"key":"10.1016\/j.placenta.2026.05.028_bib6","doi-asserted-by":"crossref","first-page":"1318","DOI":"10.1111\/jog.15241","article-title":"Histological severity of maternal and fetal inflammation is correlated with the prevalence of maternal clinical signs","volume":"48","author":"Maki","year":"2022","journal-title":"J. Obstet. Gynaecol. Res."},{"key":"10.1016\/j.placenta.2026.05.028_bib7","doi-asserted-by":"crossref","DOI":"10.1016\/j.heliyon.2020.e05698","article-title":"Clinical predictive factors of histological chorioamnionitis: case-control study","volume":"6","author":"Zaidi","year":"2020","journal-title":"Heliyon"},{"key":"10.1016\/j.placenta.2026.05.028_bib8","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1016\/j.ajog.2005.01.017","article-title":"Chorioamnionitis with a fetal inflammatory response is associated with higher neonatal mortality, morbidity, and resource use than chorioamnionitis displaying a maternal inflammatory response only","volume":"193","author":"Lau","year":"2005","journal-title":"Am. J. Obstet. Gynecol."},{"key":"10.1016\/j.placenta.2026.05.028_bib9","doi-asserted-by":"crossref","DOI":"10.1111\/aji.12986","article-title":"The role of the maternal and fetal inflammatory response in retinopathy of prematurity","volume":"80","author":"Lynch","year":"2018","journal-title":"Am. J. Reprod. Immunol."},{"key":"10.1016\/j.placenta.2026.05.028_bib10","doi-asserted-by":"crossref","first-page":"878","DOI":"10.1016\/j.jaci.2008.01.030","article-title":"Prematurity, chorioamnionitis and the development of recurrent wheezing: a prospective birth cohort Study","volume":"121","author":"Kumar","year":"2008","journal-title":"J. Allergy Clin. Immunol."},{"key":"10.1016\/j.placenta.2026.05.028_bib11","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1513\/AnnalsATS.201507-411OC","article-title":"Pulmonary morbidity in infancy after exposure to chorioamnionitis in late preterm infants","volume":"13","author":"McDowell","year":"2016","journal-title":"Ann. Am. Thorac. Soc."},{"key":"10.1016\/j.placenta.2026.05.028_bib12","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1001\/archpediatrics.2009.238","article-title":"Effect of chorioamnionitis on early childhood asthma","volume":"164","author":"Getahun","year":"2010","journal-title":"Arch. Pediatr. Adolesc. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib13","first-page":"823","article-title":"Paths of causal influence from prenatal inflammation and preterm gestation to childhood asthma symptoms","volume":"56","author":"Sindi\u010di\u0107 Dessardo","year":"2019","journal-title":"J. Asthma Off. J. Assoc. Care Asthma"},{"key":"10.1016\/j.placenta.2026.05.028_bib14","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0208302","article-title":"Maternal chorioamnionitis and neurodevelopmental outcomes in preterm and very preterm neonates: a meta-analysis","volume":"13","author":"Xiao","year":"2018","journal-title":"PLoS One"},{"key":"10.1016\/j.placenta.2026.05.028_bib15","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.placenta.2017.07.006","article-title":"The association between placental histopathology and autism spectrum disorder","volume":"57","author":"Straughen","year":"2017","journal-title":"Placenta"},{"key":"10.1016\/j.placenta.2026.05.028_bib16","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1203\/00006450-200006000-00007","article-title":"The relationship between placental and other perinatal risk factors for neurologic impairment in very low birth weight children","volume":"47","author":"Redline","year":"2000","journal-title":"Pediatr. Res."},{"key":"10.1016\/j.placenta.2026.05.028_bib17","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1016\/j.siny.2006.02.011","article-title":"Inflammatory responses in the placenta and umbilical cord","volume":"11","author":"Redline","year":"2006","journal-title":"Semin. Fetal Neonatal Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib18","first-page":"33","article-title":"Clinical chorioamnionitis at term VI: acute chorioamnionitis and funisitis according to the presence or absence of microorganisms and inflammation in the amniotic cavity","volume":"44","author":"Romero","year":"2016","journal-title":"J. Perinat. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib19","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1515\/jpm-2019-0297","article-title":"Evidence that intra-amniotic infections are often the result of an ascending invasion - a molecular microbiological study","volume":"47","author":"Romero","year":"2019","journal-title":"J. Perinat. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib20","doi-asserted-by":"crossref","first-page":"S29","DOI":"10.1016\/j.ajog.2015.08.040","article-title":"Acute chorioamnionitis and funisitis: definition, pathologic features, and clinical significance","volume":"213","author":"Kim","year":"2015","journal-title":"Am. J. Obstet. Gynecol."},{"key":"10.1016\/j.placenta.2026.05.028_bib21","doi-asserted-by":"crossref","DOI":"10.1016\/j.ajogmf.2021.100539","article-title":"Fetal and maternal inflammatory response in the setting of maternal intrapartum fever with and without clinical and histologic chorioamnionitis","volume":"4","author":"Lagodka","year":"2022","journal-title":"Am. J. Obstet. Gynecol. MFM"},{"key":"10.1016\/j.placenta.2026.05.028_bib22","doi-asserted-by":"crossref","first-page":"604.e1","DOI":"10.1016\/j.ajog.2017.02.035","article-title":"Twenty-four percent of patients with clinical chorioamnionitis in preterm gestations have no evidence of either culture-proven intraamniotic infection or intraamniotic inflammation","volume":"216","author":"Oh","year":"2017","journal-title":"Am. J. Obstet. Gynecol."},{"key":"10.1016\/j.placenta.2026.05.028_bib23","doi-asserted-by":"crossref","DOI":"10.3389\/fimmu.2020.531543","article-title":"Maternal-fetal inflammation in the placenta and the developmental origins of health and disease","volume":"11","author":"Goldstein","year":"2020","journal-title":"Front. Immunol."},{"key":"10.1016\/j.placenta.2026.05.028_bib24","doi-asserted-by":"crossref","first-page":"372","DOI":"10.5858\/arpa.2020-0753-OA","article-title":"Interobserver reliability for identifying specific patterns of placental injury as defined by the amsterdam classification","volume":"146","author":"Redline","year":"2022","journal-title":"Arch. Pathol. Lab Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib25","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1016\/S0002-9378(03)00870-6","article-title":"Intraobserver and interobserver variability for the histologic diagnosis of chorioamnionitis","volume":"190","author":"Simmonds","year":"2004","journal-title":"Am. J. Obstet. Gynecol."},{"key":"10.1016\/j.placenta.2026.05.028_bib26","doi-asserted-by":"crossref","first-page":"1116","DOI":"10.1097\/PAS.0000000000002111","article-title":"Comparison of placental pathology reports from spontaneous preterm births finalized by general surgical pathologists versus perinatal pathologist: a call to action","volume":"47","author":"Ernst","year":"2023","journal-title":"Am. J. Surg. Pathol."},{"key":"10.1016\/j.placenta.2026.05.028_bib27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4132\/jptm.2018.12.16","article-title":"Artificial intelligence in pathology","volume":"53","author":"Chang","year":"2019","journal-title":"J. Pathol. Transl. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib28","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1038\/s41374-020-00514-0","article-title":"Artificial intelligence and computational pathology","volume":"101","author":"Cui","year":"2021","journal-title":"Lab. Investig. J. Tech. Methods Pathol."},{"key":"10.1016\/j.placenta.2026.05.028_bib29","doi-asserted-by":"crossref","first-page":"930","DOI":"10.1038\/s44222-023-00096-8","article-title":"Artificial intelligence for digital and computational pathology","volume":"1","author":"Song","year":"2023","journal-title":"Nat. Rev. Bioeng."},{"key":"10.1016\/j.placenta.2026.05.028_bib30","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101813","article-title":"Deep neural network models for computational histopathology: a survey","volume":"67","author":"Srinidhi","year":"2021","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.placenta.2026.05.028_bib31","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1038\/s41591-019-0508-1","article-title":"Clinical-grade computational pathology using weakly supervised deep learning on whole slide images","volume":"25","author":"Campanella","year":"2019","journal-title":"Nat. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib32","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1038\/s41551-020-00682-w","article-title":"Data-efficient and weakly supervised computational pathology on whole-slide images","volume":"5","author":"Lu","year":"2021","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.placenta.2026.05.028_bib33","author":"Filiot"},{"key":"10.1016\/j.placenta.2026.05.028_bib34","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1038\/s41591-024-02857-3","article-title":"Towards a general-purpose foundation model for computational pathology","volume":"30","author":"Chen","year":"2024","journal-title":"Nat. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib35","author":"Zimmermann"},{"key":"10.1016\/j.placenta.2026.05.028_bib36","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1177\/10935266221137953","article-title":"Application of digital imaging and artificial intelligence to pathology of the placenta","volume":"26","author":"Marletta","year":"2023","journal-title":"Pediatr. Dev. Pathol. Off. J. Soc. Pediatr. Pathol. Paediatr. Pathol. Soc."},{"key":"10.1016\/j.placenta.2026.05.028_bib37","article-title":"AI-PLAX: AI-based placental assessment and examination using photos","volume":"84","author":"Chen","year":"2020","journal-title":"Comput. Med. Imaging Graph. Off. J. Comput. Med. Imaging Soc."},{"key":"10.1016\/j.placenta.2026.05.028_bib38","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.patrec.2020.10.004","article-title":"Multi-region saliency-aware learning for cross-domain placenta image segmentation","volume":"140","author":"Zhang","year":"2020","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.placenta.2026.05.028_bib39","doi-asserted-by":"crossref","first-page":"2111","DOI":"10.1016\/j.ajpath.2020.06.014","article-title":"Decidual vasculopathy identification in whole slide images using multiresolution hierarchical convolutional neural networks","volume":"190","author":"Clymer","year":"2020","journal-title":"Am. J. Pathol."},{"key":"10.1016\/j.placenta.2026.05.028_bib40","doi-asserted-by":"crossref","first-page":"942","DOI":"10.1038\/s41374-021-00579-5","article-title":"GestAltNet: aggregation and attention to improve deep learning of gestational age from placental whole-slide images","volume":"101","author":"Mobadersany","year":"2021","journal-title":"Lab. Investig. J. Tech. Methods Pathol."},{"key":"10.1016\/j.placenta.2026.05.028_bib41","doi-asserted-by":"crossref","first-page":"2221","DOI":"10.1038\/s41598-023-29105-x","article-title":"Multi-centre deep learning for placenta segmentation in obstetric ultrasound with multi-observer and cross-country generalization","volume":"13","author":"Andreasen","year":"2023","journal-title":"Sci. Rep."},{"key":"10.1016\/j.placenta.2026.05.028_bib42","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.placenta.2023.03.003","article-title":"Machine learning classification of placental villous infarction, perivillous fibrin deposition, and intervillous thrombus","volume":"135","author":"Goldstein","year":"2023","journal-title":"Placenta"},{"key":"10.1016\/j.placenta.2026.05.028_bib43","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.placenta.2023.11.005","article-title":"Automated detection of microscopic placental features indicative of maternal vascular malperfusion using machine learning","volume":"145","author":"Patnaik","year":"2024","journal-title":"Placenta"},{"key":"10.1016\/j.placenta.2026.05.028_bib44","article-title":"Tissue contamination challenges the credibility of machine learning models in real world digital pathology","author":"Irmakci","year":"2023","journal-title":"MedRxiv Prepr. Serv. Health Sci."},{"key":"10.1016\/j.placenta.2026.05.028_bib45","author":"Ferlaino"},{"key":"10.1016\/j.placenta.2026.05.028_bib46","doi-asserted-by":"crossref","first-page":"2710","DOI":"10.1038\/s41467-024-46986-2","article-title":"Mapping cell-to-tissue graphs across human placenta histology whole slide images using deep learning with HAPPY","volume":"15","author":"Vanea","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.placenta.2026.05.028_bib47","doi-asserted-by":"crossref","DOI":"10.1111\/aji.13944","article-title":"Quantitative modeling to characterize maternal inflammatory response of histologic chorioamnionitis in placental membranes","volume":"92","author":"Chou","year":"2024","journal-title":"Am. J. Reprod. Immunol."},{"key":"10.1016\/j.placenta.2026.05.028_bib48","series-title":"The Python Language Reference","author":"Van Rossum","year":"2020"},{"key":"10.1016\/j.placenta.2026.05.028_bib49","first-page":"10337","article-title":"Association of clinical signs of chorioamnionitis with histological chorioamnionitis and neonatal outcomes","volume":"35","author":"Ajayi","year":"2022","journal-title":"J. Matern.-Fetal Neonatal Med. Off. J. Eur. Assoc. Perinat. Med. Fed. Asia Ocean. Perinat. Soc. Int. Soc. Perinat. Obstet."},{"key":"10.1016\/j.placenta.2026.05.028_bib50","first-page":"23","article-title":"Clinical chorioamnionitis at term III: how well do clinical criteria perform in the identification of proven intra-amniotic infection?","volume":"44","author":"Romero","year":"2016","journal-title":"J. Perinat. Med."},{"key":"10.1016\/j.placenta.2026.05.028_bib51","doi-asserted-by":"crossref","first-page":"S807","DOI":"10.1016\/j.ajog.2023.02.002","article-title":"Clinical chorioamnionitis at term: definition, pathogenesis, microbiology, diagnosis, and treatment","volume":"230","author":"Jung","year":"2024","journal-title":"Am. J. Obstet. Gynecol."},{"key":"10.1016\/j.placenta.2026.05.028_bib52","article-title":"What practicing pathologists and oncologists should know about the new computational pathology\u2010based companion diagnostic tools","volume":"70045","author":"Montezuma","year":"2026","journal-title":"J. Pathol. path."},{"key":"10.1016\/j.placenta.2026.05.028_bib53","doi-asserted-by":"crossref","DOI":"10.1093\/gigascience\/giac037","article-title":"NuCLS: a scalable crowdsourcing approach and dataset for nucleus classification and segmentation in breast cancer","volume":"11","author":"Amgad","year":"2022","journal-title":"GigaScience"}],"container-title":["Placenta"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S014340042600189X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S014340042600189X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T13:25:55Z","timestamp":1789565155000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S014340042600189X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":53,"alternative-id":["S014340042600189X"],"URL":"https:\/\/doi.org\/10.1016\/j.placenta.2026.05.028","relation":{},"ISSN":["0143-4004"],"issn-type":[{"value":"0143-4004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Machine learning identification of maternal inflammatory response and systemic inflammatory response from placental membrane whole slide images","name":"articletitle","label":"Article Title"},{"value":"Placenta","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.placenta.2026.05.028","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}]}}