{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,29]],"date-time":"2026-10-29T23:46:41Z","timestamp":1793317601379,"version":"4.5.0"},"reference-count":32,"publisher":"Elsevier BV","issue":"9","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100012479","name":"General Research Fund of Shanghai Normal University","doi-asserted-by":"publisher","award":["15121524"],"award-info":[{"award-number":["15121524"]}],"id":[{"id":"10.13039\/501100012479","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing Natural Science Foundation","doi-asserted-by":"publisher","award":["CSTB2024NSCQ-MSX0314"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0314"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012669","name":"Natural Science Foundation Project of Chongqing","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010834","name":"Education Department of Hainan Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010834","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005847","name":"Health and Medical Research Fund","doi-asserted-by":"publisher","award":["07183266"],"award-info":[{"award-number":["07183266"]}],"id":[{"id":"10.13039\/501100005847","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["academicradiology.org","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Academic Radiology"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1016\/j.acra.2025.05.047","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T15:26:16Z","timestamp":1749482776000},"page":"5596-5608","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":9,"title":["Differentiating Bacterial and Non-Bacterial Pneumonia on Chest CT Using Multi-Plane Features and Clinical Biomarkers"],"prefix":"10.1016","volume":"32","author":[{"given":"Liming","family":"SONG","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuefu","family":"ZHAN","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lifeng","family":"LI","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaohua","family":"LI","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuyao","family":"WU","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mayang","family":"ZHAO","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhichun","family":"LI","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ge","family":"REN","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"CAI","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.acra.2025.05.047_bib1","article-title":"The mortality and years of life lost for community-acquired pneumonia before and during COVID-19 pandemic in China","volume":"42","author":"Fan","year":"2024","journal-title":"Lancet Reg Health West Pac"},{"key":"10.1016\/j.acra.2025.05.047_bib2","series-title":"Bacterial pneumonia","author":"Sattar","year":"2024"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib3","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1038\/s41572-021-00259-0","article-title":"Pneumonia","volume":"7","author":"Torres","year":"2021","journal-title":"Nat Rev Dis Primers"},{"issue":"6","key":"10.1016\/j.acra.2025.05.047_bib4","first-page":"625","article-title":"Community-acquired pneumonia in adults: rapid evidence review","volume":"105","author":"Womack","year":"2022","journal-title":"Am Fam Physician"},{"issue":"3","key":"10.1016\/j.acra.2025.05.047_bib5","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1097\/MCP.0000000000000567","article-title":"Computed tomography scan contribution to the diagnosis of community-acquired pneumonia","volume":"25","author":"Garin","year":"2019","journal-title":"Curr Opin Pulm Med"},{"issue":"3","key":"10.1016\/j.acra.2025.05.047_bib6","doi-asserted-by":"crossref","first-page":"E289","DOI":"10.1148\/radiol.2020202504","article-title":"Review of the chest CT differential diagnosis of ground-glass opacities in the COVID era","volume":"297","author":"Parekh","year":"2020","journal-title":"Radiology"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib7","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1148\/radiol.10101254","article-title":"Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening","volume":"259","author":"Singh","year":"2011","journal-title":"Radiology"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib8","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1378\/chest.123.1.174","article-title":"Microbiological testing and outcome of patients with severe community-acquired pneumonia","volume":"123","author":"Rello","year":"2003","journal-title":"Chest"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib9","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1007\/s44230-022-00002-2","article-title":"Review on pneumonia image detection: a machine learning approach","volume":"2","author":"Kareem","year":"2022","journal-title":"Hum Cent Intell Syst"},{"issue":"8","key":"10.1016\/j.acra.2025.05.047_bib10","doi-asserted-by":"crossref","first-page":"24101","DOI":"10.1007\/s11042-023-16419-1","article-title":"A systematic literature review on deep learning approaches for pneumonia detection using chest X-ray images","volume":"83","author":"Sharma","year":"2024","journal-title":"Multimedia Tools Appl"},{"issue":"4","key":"10.1016\/j.acra.2025.05.047_bib11","article-title":"A multimodal integration pipeline for accurate diagnosis, pathogen identification, and prognosis prediction of pulmonary infections","volume":"5","author":"Shao","year":"2024","journal-title":"Innovation (Camb)"},{"key":"10.1016\/j.acra.2025.05.047_bib12","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.105143","article-title":"Deep diagnostic agent forest (DDAF): a deep learning pathogen recognition system for pneumonia based on CT","volume":"141","author":"Chen","year":"2022","journal-title":"Comput Biol Med"},{"issue":"12","key":"10.1016\/j.acra.2025.05.047_bib13","doi-asserted-by":"crossref","first-page":"8869","DOI":"10.1007\/s00330-023-09833-4","article-title":"Pneumonia-Plus: a deep learning model for the classification of bacterial, fungal, and viral pneumonia based on CT tomography","volume":"33","author":"Wang","year":"2023","journal-title":"Eur Radiol"},{"key":"10.1016\/j.acra.2025.05.047_bib14","series-title":"International Conference on Cognitive based Information Processing and Applications","article-title":"A new pneumonia detection model based on transformer with improved self-attention mechanism","author":"Li","year":"2022"},{"key":"10.1016\/j.acra.2025.05.047_bib15","doi-asserted-by":"crossref","DOI":"10.1155\/2022\/7852958","article-title":"Multisemantic level patch merger vision transformer for diagnosis of pneumonia","volume":"2022","author":"Jiang","year":"2022","journal-title":"Comput Math Methods Med"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib16","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1186\/s13054-023-04378-w","article-title":"Serum-integrated omics reveal the host response landscape for severe pediatric community-acquired pneumonia","volume":"27","author":"Wang","year":"2023","journal-title":"Crit Care"},{"key":"10.1016\/j.acra.2025.05.047_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2021.103415","article-title":"Automatic detection of multiple types of pneumonia: open dataset and a multi-scale attention network","volume":"73","author":"Wong","year":"2022","journal-title":"Biomed Signal Process Control"},{"issue":"2","key":"10.1016\/j.acra.2025.05.047_bib18","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1007\/s00330-022-09090-x","article-title":"How do providers of artificial intelligence (AI) solutions propose and legitimize the values of their solutions for supporting diagnostic radiology workflow? a technography study in 2021","volume":"33","author":"Mehrizi","year":"2023","journal-title":"Eur Radiol"},{"issue":"6","key":"10.1016\/j.acra.2025.05.047_bib19","first-page":"1153","article-title":"Cubic convolution interpolation for digital image-processing. Ieee T acoust speech","volume":"29","author":"Keys","year":"1981"},{"issue":"5","key":"10.1016\/j.acra.2025.05.047_bib20","doi-asserted-by":"crossref","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: robust segmentation of 104 anatomic structures in CT images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiol Artif Intell"},{"issue":"2","key":"10.1016\/j.acra.2025.05.047_bib21","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat Methods"},{"key":"10.1016\/j.acra.2025.05.047_bib22","unstructured":"Tsai E., Simpson S., Lungren M.P.,\u00a0et al. (2021). Data from medical imaging data resource center (MIDRC)-RSNA international covid radiology database (RICORD) release 1C-Chest X-ray, covid+(MIDRC-RICORD-1C) (https:\/\/doi.org\/10.7937\/91ah-v663."},{"key":"10.1016\/j.acra.2025.05.047_bib23","year":"2022","journal-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition"},{"key":"10.1016\/j.acra.2025.05.047_bib24","first-page":"770","article-title":"Deep residual learning for image recognition","volume":"2016","author":"He","year":"2016","journal-title":"IEEE Confer Comput Vis Pattern Recog (Cvpr)"},{"key":"10.1016\/j.acra.2025.05.047_bib25","article-title":"Med3d: transfer learning for 3D medical image analysis","author":"Chen","year":"2019","journal-title":"arXiv preprint arXiv:190400625"},{"key":"10.1016\/j.acra.2025.05.047_bib26","article-title":"Polyloss: a polynomial expansion perspective of classification loss functions","author":"Leng","year":"2022","journal-title":"arXiv preprint arXiv:220412511"},{"key":"10.1016\/j.acra.2025.05.047_bib27","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1109\/TPAMI.2018.2858826","article-title":"Focal loss for dense object detection","volume":"42","author":"Lin","year":"2020","journal-title":"IEEE T Pattern Anal"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib28","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1186\/s12864-019-6413-7","article-title":"The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation","volume":"21","author":"Chicco","year":"2020","journal-title":"BMC Genomics"},{"issue":"6","key":"10.1016\/j.acra.2025.05.047_bib29","doi-asserted-by":"crossref","first-page":"955","DOI":"10.1016\/j.rcl.2021.06.006","article-title":"Optimization of radiology workflow with artificial intelligence","volume":"59","author":"Ranschaert","year":"2021","journal-title":"Radiol Clin"},{"issue":"4","key":"10.1016\/j.acra.2025.05.047_bib30","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1136\/ard.62.4.337","article-title":"Can procalcitonin measurement help in differentiating between bacterial infection and other kinds of inflammatory processes?","volume":"62","author":"Delevaux","year":"2003","journal-title":"Ann Rheum Dis"},{"issue":"5","key":"10.1016\/j.acra.2025.05.047_bib31","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1038\/s41591-021-01342-5","article-title":"An ensemble of neural networks provides expert-level prenatal detection of complex congenital heart disease","volume":"27","author":"Arnaout","year":"2021","journal-title":"Nat Med"},{"issue":"1","key":"10.1016\/j.acra.2025.05.047_bib32","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1038\/s41746-024-01338-8","article-title":"Spatial resolution enhancement using deep learning improves chest disease diagnosis based on thick slice CT","volume":"7","author":"Yu","year":"2024","journal-title":"NPJ Digit Med"}],"container-title":["Academic Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225005240?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1076633225005240?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T17:30:08Z","timestamp":1762363808000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1076633225005240"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":32,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["S1076633225005240"],"URL":"https:\/\/doi.org\/10.1016\/j.acra.2025.05.047","relation":{},"ISSN":["1076-6332"],"issn-type":[{"value":"1076-6332","type":"print"}],"subject":[],"published":{"date-parts":[[2025,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Differentiating Bacterial and Non-Bacterial Pneumonia on Chest CT Using Multi-Plane Features and Clinical Biomarkers","name":"articletitle","label":"Article Title"},{"value":"Academic Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.acra.2025.05.047","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 The Association of Academic Radiology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}