{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T19:44:32Z","timestamp":1791229472173,"version":"4.1.0"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"8","license":[{"start":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T00:00:00Z","timestamp":1752105600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study evaluated the influence of cognitive aids, including machine learning (ML) algorithms and checklists, on the diagnostic accuracy and confidence of dental students in detecting dental caries on bitewing radiographs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Fifty-two third-year dental students were randomly assigned to control, ML, or checklist groups. The participants recorded their caries diagnoses (charting) on 10 bitewing radiographs and rated their confidence. Diagnostic accuracy and reliability were compared between groups for caries detection (present\/absent). The inter-rater reliability for International Caries Detection and Assessment System II (ICDAS II) caries grading was assessed using weighted kappa. Participants also completed questionnaires on their perceptions of cognitive aids.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>ML group showed the highest diagnostic accuracy and confidence levels. For caries detection, the ML group achieved the highest sensitivity (79%) and diagnostic odds ratio (20.3), while the checklist group had the highest specificity (90.9%) (P\u2009&amp;lt;\u2009.001). The control group showed moderate sensitivity (67.9%) but outperformed the checklist group in this metric. Inter-rater agreement for caries detection was highest in the ML group (\u03ba\u2009=\u20090.702, 95% CI: 0.692-0.713; P\u2009&amp;lt;\u2009.001), followed by the checklist group. The ML group also had the highest weighted kappa for ICDAS II grading (\u03ba\u2009=\u20090.520, P\u2009&amp;lt;\u2009.001). Confidence levels differed significantly between groups (P\u2009&amp;lt;\u2009.001), with the ML group reporting the highest confidence.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>ML algorithms may enhance diagnostic accuracy and confidence, possibly by reducing cognitive load. While standardizing the diagnostic process, checklists were less effective, likely due to their lack of flexibility and clinical context. Further research is needed to better understand our findings and translate them into clinical workflows.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/dmfr\/twaf053","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T15:43:29Z","timestamp":1752162209000},"page":"632-641","source":"Crossref","is-referenced-by-count":13,"title":["Machine learning algorithms enhance the accuracy of radiographic diagnosis of dental caries: a comparative study"],"prefix":"10.1093","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1429-9149","authenticated-orcid":false,"given":"Shwetha","family":"Hegde","sequence":"first","affiliation":[{"name":"Dentomaxillofacial Radiology, Sydney Dental School, University of Sydney , Sydney, 2010,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5153-5393","authenticated-orcid":false,"given":"Jinlong","family":"Gao","sequence":"additional","affiliation":[{"name":"Sydney Dental School, Institute of Dental Research, Westmead Centre for Oral Health, University of Sydney , Sydney, 2145,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen","family":"Cox","sequence":"additional","affiliation":[{"name":"Discipline of Oral Surgery, Sydney Dental School, University of Sydney , Sydney, 2010,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5479-9650","authenticated-orcid":false,"given":"Shanika","family":"Nanayakkara","sequence":"additional","affiliation":[{"name":"Sydney Dental School, Institute of Dental Research, Westmead Centre for Oral Health, University of Sydney , Sydney, 2145,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0143-3812","authenticated-orcid":false,"given":"Rena","family":"Logothetis","sequence":"additional","affiliation":[{"name":"Applied Artificial Intelligence Institute, Deakin University , Melbourne, 3125,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4805-1467","authenticated-orcid":false,"given":"Rajesh","family":"Vasa","sequence":"additional","affiliation":[{"name":"Translational Research and Development, Applied Artificial Intelligence Institute, Deakin University , Melbourne, 3125,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2025,7,10]]},"reference":[{"key":"2025112613523602200_twaf053-B1","doi-asserted-by":"crossref","DOI":"10.1093\/med\/9780199366149.001.0001","volume-title":"Quality and Safety in Anesthesia and Perioperative Care","author":"Ruskin","year":"2016"},{"key":"2025112613523602200_twaf053-B2","doi-asserted-by":"publisher","first-page":"479","DOI":"10.1111\/j.1600-0722.2005.00250.x","article-title":"How dentists cope with their job demands and stay engaged: the moderating role of job resources","volume":"113","author":"Hakanen","year":"2005","journal-title":"Eur J Oral Sci"},{"key":"2025112613523602200_twaf053-B3","doi-asserted-by":"publisher","first-page":"20220279","DOI":"10.1259\/dmfr.20220279","article-title":"Factors affecting interpretation of dental radiographs","volume":"52","author":"Hegde","year":"2023","journal-title":"Dentomaxillofac Radiol"},{"key":"2025112613523602200_twaf053-B4","doi-asserted-by":"publisher","first-page":"19","DOI":"10.3406\/intel.2000.1592","article-title":"A few thoughts on cognitive overload","volume":"30","author":"Kirsh","year":"2000","journal-title":"Intellectica Rev l\u2019Association pour la Rech Cogn"},{"key":"2025112613523602200_twaf053-B5","doi-asserted-by":"publisher","first-page":"122","DOI":"10.1007\/s40746-023-00272-3","article-title":"Take a load off: understanding, measuring, and reducing cognitive load for cardiologists in high-stakes care environments","volume":"9","author":"Schaffer","year":"2023","journal-title":"Curr Treat Options Pediatr"},{"key":"2025112613523602200_twaf053-B6","doi-asserted-by":"crossref","DOI":"10.1017\/CBO9780511844744","volume-title":"Cognitive Load Theory","author":"Plass","year":"2010"},{"key":"2025112613523602200_twaf053-B7","doi-asserted-by":"publisher","first-page":"2933","DOI":"10.1007\/978-1-4419-1428-6_3","author":"Seel","year":"2012"},{"key":"2025112613523602200_twaf053-B8","doi-asserted-by":"publisher","first-page":"371","DOI":"10.3109\/0142159X.2014.889290","article-title":"Cognitive load theory: implications for medical education: AMEE Guide No. 86","volume":"36","author":"Young","year":"2014","journal-title":"Med Teach"},{"key":"2025112613523602200_twaf053-B9","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1111\/j.1365-2923.2009.03498.x","article-title":"Cognitive load theory in health professional education: design principles and strategies","volume":"44","author":"Van Merri\u00ebnboer","year":"2010","journal-title":"Med Educ"},{"key":"2025112613523602200_twaf053-B10","doi-asserted-by":"publisher","first-page":"415","DOI":"10.2147\/RMHP.S293110","article-title":"The association between cognitive medical errors and their contributing organizational and individual factors","volume":"14","author":"Alyahya","year":"2021","journal-title":"Risk Manag Healthc Policy"},{"key":"2025112613523602200_twaf053-B11","doi-asserted-by":"publisher","first-page":"611","DOI":"10.2214\/AJR.12.10375","article-title":"Cognitive and system factors contributing to diagnostic errors in radiology","volume":"201","author":"Lee","year":"2013","journal-title":"AJR Am J Roentgenol"},{"key":"2025112613523602200_twaf053-B12","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1111\/odi.14516","article-title":"WHO\u2019s global oral health status report 2022: actions, discussion and implementation","volume":"30","author":"Jain","year":"2024","journal-title":"Oral Dis"},{"key":"2025112613523602200_twaf053-B13","author":"Australian Institute of Health and Welfare","year":"2024"},{"key":"2025112613523602200_twaf053-B14","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/0300-5712(93)90022-I","article-title":"Developments in radiographic caries diagnosis","volume":"21","author":"Wenzel","year":"1993","journal-title":"J Dent"},{"key":"2025112613523602200_twaf053-B15","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1002\/j.0022-0337.2001.65.10.tb03474.x","article-title":"Radiographic diagnosis of dental caries","volume":"65","author":"Dove","year":"2001","journal-title":"J Dent Educ"},{"key":"2025112613523602200_twaf053-B16","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1159\/000016454","article-title":"Reliability of visual examination, fibre-optic transillumination, and bite-wing radiography, and reproducibility of direct visual examination following tooth separation for the identification of cavitated carious lesions in contacting approximal surfaces","volume":"32","author":"Hintze","year":"1998","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B17","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1259\/dmfr\/30526171","article-title":"Proximal caries detection accuracy using intraoral bitewing radiography, extraoral bitewing radiography and panoramic radiography","volume":"41","author":"Kamburoglu","year":"2012","journal-title":"Dentomaxillofac Radiol"},{"key":"2025112613523602200_twaf053-B18","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1038\/sj.dmfr.4600652","article-title":"Comparing the accuracy of Dutch dentists and dental students in the radiographic diagnosis of dentinal caries","volume":"31","author":"Mileman","year":"2002","journal-title":"Dentomaxillofac Radiol"},{"key":"2025112613523602200_twaf053-B19","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1159\/000485807","article-title":"The influence of cognitive bias on caries lesion detection in preschool children","volume":"52","author":"Moro","year":"2018","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B20","doi-asserted-by":"publisher","first-page":"355","DOI":"10.1159\/000262092","article-title":"Radiographic evaluation of occlusal caries: effect of training and experience","volume":"29","author":"Lazarchik","year":"1995","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B21","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1038\/s41432-019-0043-4","article-title":"Does time pressure impact on dentists\u2019 diagnostic performance?","volume":"20","author":"Cave","year":"2019","journal-title":"Evid Based Dent"},{"key":"2025112613523602200_twaf053-B22","doi-asserted-by":"publisher","first-page":"506","DOI":"10.1016\/0030-4220(90)90387-8","article-title":"Prediction of efficacy of bitewing radiographs for caries detection","volume":"69","author":"White","year":"1990","journal-title":"Oral Surgery, Oral Med Oral Pathol"},{"key":"2025112613523602200_twaf053-B23","doi-asserted-by":"publisher","first-page":"20210010","DOI":"10.1259\/dmfr.20210010","article-title":"Radiographic modalities for diagnosis of caries in a historical perspective: from film to machine-intelligence supported systems","volume":"50","author":"Wenzel","year":"2021","journal-title":"Dentomaxillofac Radiol"},{"key":"2025112613523602200_twaf053-B24","doi-asserted-by":"publisher","first-page":"103226","DOI":"10.1016\/j.jdent.2019.103226","article-title":"Convolutional neural networks for dental image diagnostics: a scoping review","volume":"91","author":"Schwendicke","year":"2019","journal-title":"J Dent"},{"key":"2025112613523602200_twaf053-B25","doi-asserted-by":"publisher","first-page":"924","DOI":"10.1016\/j.jdent.2015.02.009","article-title":"Radiographic caries detection: a systematic review and meta-analysis","volume":"43","author":"Schwendicke","year":"2015","journal-title":"J Dent"},{"key":"2025112613523602200_twaf053-B26","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1159\/000099314","article-title":"Risk factors for a false positive test outcome in diagnosis of caries in approximal surfaces: impact of radiographic modality and observer characteristics","volume":"41","author":"Wenzel","year":"2007","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B27","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1111\/j.1600-0722.2006.00383.x","article-title":"Dental caries paradigms in diagnosis and diagnostic research","volume":"114","author":"Baelum","year":"2006","journal-title":"Eur J Oral Sci"},{"key":"2025112613523602200_twaf053-B28","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1159\/000261640","article-title":"Variations among dentists in radiographic detection of occlusal caries","volume":"28","author":"Espelid","year":"1994","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B29","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1016\/j.cden.2021.02.002","article-title":"Radiology of dental caries","volume":"65","author":"Dayo","year":"2021","journal-title":"Dent Clin North Am"},{"key":"2025112613523602200_twaf053-B30","doi-asserted-by":"publisher","first-page":"106","DOI":"10.1016\/j.jdent.2018.07.015","article-title":"Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm","volume":"77","author":"Lee","year":"2018","journal-title":"J Dent"},{"key":"2025112613523602200_twaf053-B31","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1159\/000061642","article-title":"Characterization and validation of diagnostic methods","volume":"17","author":"ten Bosch","year":"2000","journal-title":"Monogr Oral Sci"},{"key":"2025112613523602200_twaf053-B32","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1111\/anae.15939","article-title":"Cognitive aids in the management of clinical emergencies: a systematic review","volume":"78","author":"Greig","year":"2023","journal-title":"Anaesthesia"},{"key":"2025112613523602200_twaf053-B33","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1097\/01.CCM.0000142399.70913.2F","article-title":"Eliminating catheter-related bloodstream infections in the intensive care unit","volume":"32","author":"Berenholtz","year":"2004","journal-title":"Crit Care Med"},{"key":"2025112613523602200_twaf053-B34","doi-asserted-by":"publisher","first-page":"e26300","DOI":"10.5812\/aamp.26300v2","article-title":"Checklists and other cognitive aids for emergency and routine anesthesia care-a survey on the perception of anesthesia providers from a large academic US institution","volume":"5","author":"Krombach","year":"2015","journal-title":"Anesthesiol Pain Med"},{"key":"2025112613523602200_twaf053-B35","doi-asserted-by":"publisher","first-page":"1668","DOI":"10.1148\/rg.2015150023","article-title":"Understanding and confronting our mistakes: the epidemiology of error in radiology and strategies for error reduction","volume":"35","author":"Bruno","year":"2015","journal-title":"Radiographics"},{"key":"2025112613523602200_twaf053-B36","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1097\/ACM.0b013e31820824cd","article-title":"Checklists to reduce diagnostic errors","volume":"86","author":"Ely","year":"2011","journal-title":"Acad Med"},{"key":"2025112613523602200_twaf053-B37","first-page":"223","author":"Ali","year":"2016"},{"key":"2025112613523602200_twaf053-B38","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1111\/ger.12432","article-title":"Application of machine learning for diagnostic prediction of root caries","volume":"36","author":"Hung","year":"2019","journal-title":"Gerodontology"},{"key":"2025112613523602200_twaf053-B39","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1111\/j.1834-7819.2009.01165.x","article-title":"The caries management system: an evidence-based preventive strategy for dental practitioners. Application for children and adolescents","volume":"54","author":"Evans","year":"2009","journal-title":"Aust Dent J"},{"key":"2025112613523602200_twaf053-B40","volume-title":"Essentials of Dental Radiography and Radiology","author":"Whaites","year":"2013"},{"key":"2025112613523602200_twaf053-B41","author":"Press Release"},{"key":"2025112613523602200_twaf053-B42","doi-asserted-by":"publisher","first-page":"503","DOI":"10.1159\/000527491","article-title":"Diagnosis of interproximal caries lesions in bitewing radiographs using a deep convolutional neural network-based software","volume":"56","author":"Garc\u00eda-Ca\u00f1as","year":"2022","journal-title":"Caries Res"},{"key":"2025112613523602200_twaf053-B43","doi-asserted-by":"publisher","first-page":"20180051","DOI":"10.1259\/dmfr.20180051","article-title":"Tooth detection and numbering in panoramic radiographs using convolutional neural networks","volume":"48","author":"Tuzoff","year":"2019","journal-title":"Dentomaxillofac Radiol"},{"key":"2025112613523602200_twaf053-B44","first-page":"82","article-title":"A review of statistical outlier methods","volume":"30","author":"Walfish","year":"2006","journal-title":"Pharm Technol"},{"key":"2025112613523602200_twaf053-B45","doi-asserted-by":"publisher","first-page":"159","DOI":"10.2307\/2529310","article-title":"The measurement of observer agreement for categorical data","volume":"33","author":"Landis","year":"1977","journal-title":"Biometrics"},{"key":"2025112613523602200_twaf053-B46","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1136\/bmjqs-2012-001797","article-title":"Surgical checklists: a systematic review of impacts and implementation","volume":"23","author":"Treadwell","year":"2014","journal-title":"BMJ Qual Saf"},{"key":"2025112613523602200_twaf053-B47","doi-asserted-by":"publisher","first-page":"e058219","DOI":"10.1136\/bmjopen-2021-058219","article-title":"Checklists to reduce diagnostic error: a systematic review of the literature using a human factors framework","volume":"12","author":"Al-Khafaji","year":"2022","journal-title":"BMJ Open"},{"key":"2025112613523602200_twaf053-B48","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1145\/3582431","article-title":"Transitioning cognitive aids into decision support platforms: requirements and design guidelines","volume":"30","author":"Mastrianni","year":"2023","journal-title":"ACM Trans Comput Interact"},{"key":"2025112613523602200_twaf053-B49","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s12875-017-0650-0","article-title":"Managing diagnostic uncertainty in primary care: a systematic critical review","volume":"18","author":"Alam","year":"2017","journal-title":"BMC Fam Pract"},{"key":"2025112613523602200_twaf053-B50","doi-asserted-by":"publisher","first-page":"274","DOI":"10.1186\/s12903-024-04046-7","article-title":"Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review","volume":"24","author":"Albano","year":"2024","journal-title":"BMC Oral Health"},{"key":"2025112613523602200_twaf053-B51","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1111\/bioe.12957","article-title":"How competitors become collaborators\u2014Bridging the gap(s) between machine learning algorithms and clinicians","volume":"36","author":"Grote","year":"2022","journal-title":"Bioethics"},{"key":"2025112613523602200_twaf053-B52","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1038\/s41591-020-0942-0","article-title":"Human\u2013computer collaboration for skin cancer recognition","volume":"26","author":"Tschandl","year":"2020","journal-title":"Nat Med"},{"key":"2025112613523602200_twaf053-B53","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1186\/s41747-024-00474-w","article-title":"Sample size calculation for data reliability and diagnostic performance: a go-to review","volume":"8","author":"Monti","year":"2024","journal-title":"Eur Radiol Exp"},{"key":"2025112613523602200_twaf053-B54","doi-asserted-by":"publisher","first-page":"124","DOI":"10.1111\/adj.12812","article-title":"Promises and perils of artificial intelligence in dentistry","volume":"66","author":"Pethani","year":"2021","journal-title":"Aust Dent J"}],"container-title":["Dentomaxillofacial Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/dmfr\/advance-article-pdf\/doi\/10.1093\/dmfr\/twaf053\/63723997\/twaf053.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/dmfr\/article-pdf\/54\/8\/632\/63723997\/twaf053.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/dmfr\/article-pdf\/54\/8\/632\/63723997\/twaf053.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T18:52:44Z","timestamp":1764183164000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/dmfr\/article\/54\/8\/632\/8196213"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,10]]},"references-count":54,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2025,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/dmfr\/twaf053","relation":{},"ISSN":["0250-832X","1476-542X"],"issn-type":[{"value":"0250-832X","type":"print"},{"value":"1476-542X","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,11]]},"published":{"date-parts":[[2025,7,10]]}}}