{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T16:45:40Z","timestamp":1792601140304,"version":"4.5.0"},"reference-count":22,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2027,3,1]],"date-time":"2027-03-01T00:00:00Z","timestamp":1803859200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100003392","name":"Fujian Provincial Natural Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003392","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010166","name":"Xiamen City Department of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Clinica Chimica Acta"],"published-print":{"date-parts":[[2027,3]]},"DOI":"10.1016\/j.cca.2026.122912","type":"journal-article","created":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T14:56:19Z","timestamp":1792248979000},"page":"122912","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["ThaCoder: an explainable deep learning framework for thalassemia screening using routine complete blood count: a multi-center validation study"],"prefix":"10.1016","volume":"594","author":[{"given":"Xiaosong","family":"Su","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kouqiong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuning","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baishen","family":"Pan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beili","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaye","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.cca.2026.122912_bb0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.eclinm.2024.102619","article-title":"Global, regional, and national burden of thalassemia, 1990-2021: a systematic analysis for the global burden of disease study 2021","volume":"72","author":"Tuo","year":"2024","journal-title":"EClinicalMedicine"},{"key":"10.1016\/j.cca.2026.122912_bb0010","doi-asserted-by":"crossref","DOI":"10.3389\/frhem.2023.1187681","article-title":"Global burden and unmet needs in the treatment of transfusion-dependent \u03b2-thalassemia","volume":"2","author":"Forni","year":"2023","journal-title":"Front. Hematol."},{"key":"10.1016\/j.cca.2026.122912_bb0015","doi-asserted-by":"crossref","DOI":"10.3389\/fmolb.2020.00074","article-title":"Update in laboratory diagnosis of thalassemia","volume":"7","author":"Munkongdee","year":"2020","journal-title":"Front. Mol. Biosci."},{"key":"10.1016\/j.cca.2026.122912_bb0020","series-title":"Prevention of Thalassaemias and Other Haemoglobin Disorders: Volume 2: Laboratory Protocols","author":"Old","year":"2012"},{"key":"10.1016\/j.cca.2026.122912_bb0025","doi-asserted-by":"crossref","DOI":"10.3389\/fped.2022.1015769","article-title":"Applications of next generation sequencing in the screening and diagnosis of thalassemia: a mini-review","volume":"10","author":"Suhaimi","year":"2022","journal-title":"Front. Pediatr."},{"issue":"0","key":"10.1016\/j.cca.2026.122912_bb0030","doi-asserted-by":"crossref","first-page":"S39","DOI":"10.5045\/br.2021.2020332","article-title":"Molecular basis and diagnosis of thalassemia","volume":"56","author":"Lee","year":"2021","journal-title":"Blood Res."},{"key":"10.1016\/j.cca.2026.122912_bb0035","article-title":"A comparative review on machine and deep learning techniques for thalassemia identification and classification","volume":"10","author":"Kaur","year":"2025","journal-title":"J. Inf. Syst. Eng"},{"key":"10.1016\/j.cca.2026.122912_bb0040","doi-asserted-by":"crossref","DOI":"10.33022\/ijcs.v13i3.4035","article-title":"Machine learning-based prediction of thalassemia: a review","volume":"13","author":"Abdulkarim","year":"2024","journal-title":"Indones. J. Comput. Sci."},{"issue":"22","key":"10.1016\/j.cca.2026.122912_bb0045","doi-asserted-by":"crossref","DOI":"10.3390\/diagnostics13223441","article-title":"Predicting thalassemia using feature selection techniques: a comparative analysis","volume":"13","author":"Saleem","year":"2023","journal-title":"Diagnostics"},{"key":"10.1016\/j.cca.2026.122912_bb0050","doi-asserted-by":"crossref","DOI":"10.1016\/j.cca.2024.120025","article-title":"Multithal-classifier, a machine learning-based multi-class model for thalassemia diagnosis and classification","volume":"567","author":"Wang","year":"2025","journal-title":"Clin. Chim. Acta"},{"issue":"9","key":"10.1016\/j.cca.2026.122912_bb0055","doi-asserted-by":"crossref","first-page":"1551","DOI":"10.3390\/diagnostics13091551","article-title":"Applications of artificial intelligence in thalassemia: a comprehensive review","volume":"13","author":"Ferih","year":"2023","journal-title":"Diagnostics"},{"key":"10.1016\/j.cca.2026.122912_bb0060","doi-asserted-by":"crossref","DOI":"10.1016\/j.cca.2023.117329","article-title":"Predicting thalassemia using deep neural network based on red blood cell indices","volume":"543","author":"Mo","year":"2023","journal-title":"Clin. Chim. Acta"},{"issue":"1","key":"10.1016\/j.cca.2026.122912_bb0065","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1038\/s41746-025-01766-0","article-title":"Development and validation of an interpretable risk prediction model for the early classification of thalassemia","volume":"8","author":"Lai","year":"2025","journal-title":"NPJ Digit. Med."},{"issue":"1","key":"10.1016\/j.cca.2026.122912_bb0070","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1111\/ijlh.70017","article-title":"Machine learning-based prediction of \u03b2-thalassemia trait using red blood cell indices","volume":"48","author":"Payda\u015f Hataysal","year":"2026","journal-title":"Int. J. Lab. Hematol."},{"issue":"1","key":"10.1016\/j.cca.2026.122912_bb0075","doi-asserted-by":"crossref","first-page":"36717","DOI":"10.1038\/s41598-025-20605-6","article-title":"Machine learning improves detection of alpha thalassemia carriers compared to clinical features","volume":"15","author":"Mohammadi","year":"2025","journal-title":"Sci. Rep."},{"key":"10.1016\/j.cca.2026.122912_bb0080","doi-asserted-by":"crossref","first-page":"108581","DOI":"10.1016\/j.cmpb.2024.108581","article-title":"Classification of \u03b1-thalassemia data using machine learning models","volume":"260","author":"Christensen","year":"2025","journal-title":"Comput. Methods Prog. Biomed."},{"issue":"1","key":"10.1016\/j.cca.2026.122912_bb0085","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1007\/s10803-009-0816-2","article-title":"Evaluating the use of exploratory factor analysis in developmental disability psychological research","volume":"40","author":"Norris","year":"2010","journal-title":"J. Autism Dev. Disord."},{"key":"10.1016\/j.cca.2026.122912_bb0090","doi-asserted-by":"crossref","unstructured":"Liu M, Zhou J, Xi Q, Liang Y, Li H, Liang P, et al. A computational framework of routine test data for the cost-effective chronic disease prediction. Brief. Bioinform. 2023;24(2).","DOI":"10.1093\/bib\/bbad054"},{"issue":"12","key":"10.1016\/j.cca.2026.122912_bb0095","doi-asserted-by":"crossref","first-page":"1197","DOI":"10.1038\/s41551-020-00633-5","article-title":"Open resource of clinical data from patients with pneumonia for the prediction of COVID-19 outcomes via deep learning","volume":"4","author":"Ning","year":"2020","journal-title":"Nat. Biomed. Eng."},{"key":"10.1016\/j.cca.2026.122912_bb0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.artint.2021.103502","article-title":"Explaining individual predictions when features are dependent: more accurate approximations to Shapley values","volume":"298","author":"Aas","year":"2021","journal-title":"Artif. Intell."},{"key":"10.1016\/j.cca.2026.122912_bb0105","series-title":"Shapley Explainability on the Data Manifold","author":"Frye","year":"2021"},{"key":"10.1016\/j.cca.2026.122912_bb0110","series-title":"A unified approach to interpreting model predictions","author":"Lundberg","year":"2017"}],"container-title":["Clinica Chimica Acta"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0009898126020942?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0009898126020942?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T16:20:43Z","timestamp":1792599643000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0009898126020942"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2027,3]]},"references-count":22,"alternative-id":["S0009898126020942"],"URL":"https:\/\/doi.org\/10.1016\/j.cca.2026.122912","relation":{},"ISSN":["0009-8981"],"issn-type":[{"value":"0009-8981","type":"print"}],"subject":[],"published":{"date-parts":[[2027,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"ThaCoder: an explainable deep learning framework for thalassemia screening using routine complete blood count: a multi-center validation study","name":"articletitle","label":"Article Title"},{"value":"Clinica Chimica Acta","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cca.2026.122912","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"122912"}}