{"check_arguments":{"unspecified":[],"unsupported":[]},"function":"recommend_papers","inputs":{"fields":"title,citationCount","id":"CorpusId:10491450","recommend_method":"combined,s2_api"},"jj":{"recommendedPapers":[{"authors":[{"authorId":"2200356803","name":"M. B\u00fcttner"},{"authorId":"2100386974","name":"R. Rokhshad"},{"authorId":"2181727013","name":"Janet Brinz"},{"authorId":"2292013950","name":"Julien Issa"},{"authorId":"39339273","name":"A. Chaurasia"},{"authorId":"145212927","name":"S. Uribe"},{"authorId":"2316914680","name":"Tedy Karteva"},{"authorId":"2316916831","name":"Sanaa Chala"},{"authorId":"101567878","name":"A. Tich\u00fd"},{"authorId":"5747104","name":"F. Schwendicke"}],"citationCount":26,"externalIds":{"CorpusId":271952560,"DOI":"10.1016/j.jdent.2024.105318","PubMed":"39182639"},"paperId":"162ba32fc3d12a4d1707245b770f4a9d99350b23","referenceCount":14,"title":"Core Outcomes Measures in Dental Computer Vision Studies (DentalCOMS).","year":2024},{"authors":[{"authorId":"2364488010","name":"Nicole Rodrigues"},{"authorId":"2185785107","name":"M. Bonfanti-Gris"},{"authorId":"2260008931","name":"Shizhu Bai"},{"authorId":"2258320914","name":"G. Pradi\u0301es"},{"authorId":"32220880","name":"M. P. Salido"}],"citationCount":1,"externalIds":{"CorpusId":283173527,"DOI":"10.1016/j.jdent.2025.106252","PubMed":"41270951"},"paperId":"49dbb04ddb197831a75e95f96d74152260d21192","referenceCount":27,"title":"Longitudinal Assessment of an AI-Based Software for Interproximal Caries Detection in Bitewing Radiographs.","year":2025},{"authors":[{"authorId":"2364852962","name":"A. Malik"},{"authorId":"2367358952","name":"Adeel-ur-Rehman"},{"authorId":"2368187485","name":"Saad Umar"},{"authorId":"2265015281","name":"Muhammad Zubair"},{"authorId":"2368187675","name":"Zainab Sajjad"},{"authorId":"2368178961","name":"Ali Ghaffar"},{"authorId":"2368180335","name":"Muhammad Jalil"}],"citationCount":1,"externalIds":{"CorpusId":279550070,"DOI":"10.71000/fdmjfp07"},"paperId":"594eb0c98fb833dfe92a1ebfef540af992e2426b","referenceCount":0,"title":"DIAGNOSTIC ACCURACY OF AI-BASED VERSUS CONVENTIONAL RADIOGRAPHIC CARIES DETECTION IN PEDIATRIC PATIENTS: A CROSS-SECTIONAL STUDY","year":2025},{"authors":[{"authorId":"2275809014","name":"Carolina Ganss"},{"authorId":"6742464","name":"K. Vach"}],"citationCount":0,"externalIds":{"CorpusId":286901246,"DOI":"10.1159/000551765"},"paperId":"d2ceebf727119fb07228012c84f593d2b62ec3de","referenceCount":0,"title":"Rethinking diagnostic performance metrics in imaging AI: lessons from caries detection on radiographs","year":2026},{"authors":[{"authorId":"36273211","name":"Nour Ammar"},{"authorId":"2253794705","name":"J. K\u00fchnisch"}],"citationCount":31,"externalIds":{"CorpusId":268226880,"DOI":"10.1016/j.jdsr.2024.02.001","PubMed":"38450159","PubMedCentral":"10917640"},"paperId":"fcbb9da3df25a833d53af63aa12d06fc0b5bfe7f","referenceCount":39,"title":"Diagnostic performance of artificial intelligence-aided caries detection on bitewing radiographs: a systematic review and meta-analysis","year":2024},{"authors":[{"authorId":"52225633","name":"W. Panyarak"},{"authorId":"2975670","name":"W. Suttapak"},{"authorId":"3028129","name":"K. Wantanajittikul"},{"authorId":"6206213","name":"Arnon Charuakkra"},{"authorId":"5734489","name":"S. Prapayasatok"}],"citationCount":1,"externalIds":{"CorpusId":255941073,"DOI":"10.1007/s00784-023-04865-y","PubMed":"36648585"},"paperId":"628895e6e961b239ceb0b6764fab69c26b6ba818","referenceCount":0,"title":"Correction to: Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS\u2122 radiographic scoring system","year":2023},{"authors":[{"authorId":"2343723914","name":"Ricardo E. Gonzalez-Valenzuela"},{"authorId":"2329084188","name":"Pascal Mettes"},{"authorId":"2265480518","name":"B. Loos"},{"authorId":"2802315","name":"H. Marquering"},{"authorId":"2328381001","name":"Erwin Berkhout"}],"citationCount":2,"externalIds":{"CorpusId":283479051,"DOI":"10.1007/s00784-025-06672-z","PubMed":"41339765","PubMedCentral":"12675547"},"paperId":"a6e37611a1c2a97def65a9a5bfc57fc90cce6d9e","referenceCount":53,"title":"Accuracy of deep learning-based AI models for early caries lesion detection: the influence of annotation quality and reference choice","year":2025},{"authors":[{"authorId":"2154780638","name":"H. G. G\u00fcne\u00e7"},{"authorId":"151479653","name":"Elif \u015eeyda \u00dcrkmez"},{"authorId":"2163335708","name":"Aleyna Danac\u0131"},{"authorId":"2334274615","name":"E. Dilmac"},{"authorId":"2163335350","name":"H\u00fcseyin Onay"},{"authorId":"1416738166","name":"Kader Cesur Ayd\u0131n"}],"citationCount":29,"externalIds":{"CorpusId":264531655,"DOI":"10.21037/qims-23-762","PubMed":"37969638","PubMedCentral":"10644137"},"paperId":"bb3d4feacad89d93bcb47e66de8b6e195b895b34","referenceCount":29,"title":"Comparison of artificial intelligence vs. junior dentists\u2019 diagnostic performance based on caries and periapical infection detection on panoramic images","year":2023},{"authors":[{"authorId":"2294328928","name":"Julian Boldt"},{"authorId":"49524748","name":"M. Schuster"},{"authorId":"2255004086","name":"G. Krastl"},{"authorId":"2285369857","name":"Marc Schmitter"},{"authorId":"2309323965","name":"Jonas Pfundt"},{"authorId":"2309323884","name":"A. Stellzig-Eisenhauer"},{"authorId":"2220205238","name":"F. Kunz"}],"citationCount":10,"externalIds":{"CorpusId":270889181,"DOI":"10.3390/jcm13133846","PubMed":"38999411","PubMedCentral":"11242122"},"paperId":"8f5c6899ee1d5b0825f23862082c168b92115c66","referenceCount":61,"title":"Developing the Benchmark: Establishing a Gold Standard for the Evaluation of AI Caries Diagnostics","year":2024},{"authors":[{"authorId":"153355218","name":"W. Ahmed"},{"authorId":"2209381313","name":"Amr Ahmed Azhari"},{"authorId":"2332671325","name":"Rabab A. Alnakhli"},{"authorId":"2365560628","name":"Y. Alsulami"},{"authorId":"114950150","name":"Yasser Merdad"},{"authorId":"12591275","name":"M. AbdelRazek"},{"authorId":"2373437032","name":"Talaat Sahlol"}],"citationCount":2,"externalIds":{"CorpusId":280291461,"DOI":"10.1016/j.prosdent.2025.06.020","PubMed":"40664593"},"paperId":"f5a9f2a6c392bb9f966992d4ab1f69f6fdebdaa0","referenceCount":0,"title":"Development and evaluation of an artificial intelligence (AI) model for detecting dental caries from 3D intraoral scans.","year":2025},{"authors":[{"authorId":"1576838295","name":"E. Chaves"},{"authorId":"79401780","name":"J. Teunis"},{"authorId":"2045216599","name":"V. H. Digmayer Romero"},{"authorId":"2349011054","name":"N. van Nistelrooij"},{"authorId":"134768670","name":"S. Vinayahalingam"},{"authorId":"2408505164","name":"D. Sezen-Hulsmans"},{"authorId":"2121791492","name":"F. M. Mendes"},{"authorId":"2195372765","name":"Martina Huysmans"},{"authorId":"2273783219","name":"M. Cenci"},{"authorId":"2088702880","name":"G. D. S. Lima"}],"citationCount":0,"externalIds":{"CorpusId":287767528,"DOI":"10.64898/2026.04.17.26350883"},"paperId":"d24b52f546987e97711d03681b8408ea8072c73e","referenceCount":0,"title":"AI-Based Clinical Decision Support Systems for Secondary Caries on Bitewings: A Multi-Algorithm Comparison","year":2026},{"authors":[{"authorId":"32112346","name":"H. Baseri"},{"authorId":"3337586","name":"R. Rafeh"},{"authorId":"72065504","name":"F. S. Tafreshi"},{"authorId":"5774154","name":"M. Houshyar"},{"authorId":"80780081","name":"Khojastepour Leila"}],"citationCount":4,"externalIds":{"CorpusId":74108989,"MAG":"2254410411"},"paperId":"04c1db0ac74316189b05cb4d7aef2e3bf19135a7","referenceCount":35,"title":"Introducing a Dental Caries Marking Software and Evaluate Radiologists\u2019 Disagreement in Caries Detection Using this Software","year":2015},{"authors":[{"authorId":"5490906","name":"S. N. Basheer"},{"authorId":"1657177616","name":"Arwa A Daghrery"},{"authorId":"2044762158","name":"N. Albar"},{"authorId":"5645180","name":"S. Peeran"},{"authorId":"115550036","name":"M. Karobari"}],"citationCount":0,"externalIds":{"CorpusId":285344731,"DOI":"10.1038/s41432-026-01207-1","PubMed":"41652112"},"paperId":"38890e238a74fd182b213707a73f8512241c594f","referenceCount":50,"title":"Emerging trends in the early diagnosis of dental caries: a scoping review of artificial intelligence, digital diagnostics, and teledentistry.","year":2026},{"authors":[{"authorId":"2310310984","name":"Elisabeth Frenkel"},{"authorId":"2310310986","name":"Julia Neumayr"},{"authorId":"2310310451","name":"Julia Schwarzmaier"},{"authorId":"2310308342","name":"Andreas Kessler"},{"authorId":"36273211","name":"Nour Ammar"},{"authorId":"5747104","name":"F. Schwendicke"},{"authorId":"2253794705","name":"J. K\u00fchnisch"},{"authorId":"2204207007","name":"H. Dujic"}],"citationCount":5,"externalIds":{"CorpusId":273355574,"DOI":"10.3390/diagnostics14202281","PubMed":"39451605","PubMedCentral":"11507311"},"paperId":"87654a0a5bf3baca9d5761786b376e0b39513977","referenceCount":35,"title":"Caries Detection and Classification in Photographs Using an Artificial Intelligence-Based Model\u2014An External Validation Study","year":2024},{"authors":[{"authorId":"2310310451","name":"Julia Schwarzmaier"},{"authorId":"2310310984","name":"Elisabeth Frenkel"},{"authorId":"2310310986","name":"Julia Neumayr"},{"authorId":"36273211","name":"Nour Ammar"},{"authorId":"2310308342","name":"Andreas Kessler"},{"authorId":"5747104","name":"F. Schwendicke"},{"authorId":"2253794705","name":"J. K\u00fchnisch"},{"authorId":"2204207007","name":"H. Dujic"}],"citationCount":12,"externalIds":{"CorpusId":272379311,"DOI":"10.3390/jcm13175215","PubMed":"39274428","PubMedCentral":"11396146"},"paperId":"9b7a08c5387f1f81a1ac3e5f5d50e5f87065c954","referenceCount":38,"title":"Validation of an Artificial Intelligence-Based Model for Early Childhood Caries Detection in Dental Photographs","year":2024},{"authors":[{"authorId":"2228261063","name":"S. Rodr\u00edguez"}],"citationCount":0,"externalIds":{"CorpusId":276077484},"paperId":"a02bce1269eb2584e95f0c30607f2a29231496b2","referenceCount":29,"title":"Current Trends in Modern Dentistry: Diagnostic Sensitivity of AI in Detecting Dental Conditions. A Systematic Review and Meta-Analysis","year":null},{"authors":[{"authorId":"2378499697","name":"P. Madan Kumar"},{"authorId":"2381484560","name":"SA Sivakumar"},{"authorId":"2381509700","name":"S. Rajeshwari"},{"authorId":"2338085648","name":"C. Lavanya"},{"authorId":"2381501718","name":"K. Ranganathan"}],"citationCount":2,"externalIds":{"CorpusId":282898896,"DOI":"10.1016/j.jobcr.2025.10.027","PubMed":"41737530"},"paperId":"cd1b5415d6b2316c8bd2e6a30f318ea90900505f","referenceCount":36,"title":"Diagnostic efficiency of digital photography and AI-assisted image interpretation in dental caries examination: An umbrella review.","year":2026},{"authors":[{"authorId":"2371155710","name":"Kaixin Guo"},{"authorId":"2402811451","name":"Madeline Jun Yu Yon"},{"authorId":"46286231","name":"Yanqi Yang"},{"authorId":"2238649779","name":"C. McGrath"},{"authorId":"1483576045","name":"P. Lam"}],"citationCount":0,"externalIds":{"CorpusId":284502364,"DOI":"10.1016/j.jebdp.2025.102225","PubMed":"41833430"},"paperId":"b72fd2c07fbe58c64377d59ceef53d5c2bbb1770","referenceCount":63,"title":"DIAGNOSTIC PERFORMANCE OF MACHINE LEARNING-AIDED PROXIMAL CARIES DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS.","year":2026},{"authors":[{"authorId":"2321912611","name":"Jarupat Jundaeng"},{"authorId":"1722160","name":"R. Chamchong"},{"authorId":"2392184265","name":"Chaemchan Thessingha"},{"authorId":"11037019","name":"C. Nithikathkul"}],"citationCount":0,"externalIds":{"CorpusId":282979916,"DOI":"10.1177/23202068251390681"},"paperId":"008ebf1fc4d35e2bd5f3c30e86f8f2455e7993d2","referenceCount":44,"title":"Precision and Accessibility in Periodontal Diagnosis: A Comparative Study of AI and Clinical Expertise","year":2025},{"authors":[{"authorId":"2354349381","name":"Kaijing Mao"},{"authorId":"41130013","name":"K. M. Thu"},{"authorId":"2257978511","name":"K. Hung"},{"authorId":"27097759","name":"O. Yu"},{"authorId":"13896425","name":"R. T. Hsung"},{"authorId":"1951017","name":"W. Y. Lam"}],"citationCount":10,"externalIds":{"CorpusId":279995849,"DOI":"10.1016/j.identj.2025.100883","PubMed":"40639137","PubMedCentral":"12274314"},"paperId":"126235da89ab7089eead15ed5c36153bf89eeb2e","referenceCount":91,"title":"Artificial Intelligence in Detecting Periodontal Disease From Intraoral Photographs: A Systematic Review","year":2025}]},"limit":20,"my_id":10491450,"recommendations":{"combined":{"ids":["CorpusId:29970479","CorpusId:13388982","CorpusId:136173202","CorpusId:42957386","CorpusId:24973379","CorpusId:225723591","CorpusId:25852603","CorpusId:74725626","CorpusId:59307605","CorpusId:18636926","CorpusId:14425869","CorpusId:21041004","CorpusId:209186342","CorpusId:135989269","CorpusId:72894723","CorpusId:8415779","CorpusId:91795498","CorpusId:71456752","CorpusId:23930302","CorpusId:247464335"],"papers":[{"bibtex":null,"citationCount":27,"paperId":"833464ff30a83cf484d7943a236367278a1f4e62","pdfs":[],"title":"Reliability of the Nyvad criteria for caries assessment in primary teeth."},{"bibtex":null,"citationCount":89,"paperId":"7b9abbbc083a8f63ce1262dc2b513741a0415b2d","pdfs":[],"title":"Clinical Performance of Two Visual Scoring Systems in Detecting and Assessing Activity Status of Occlusal Caries in Primary Teeth"},{"bibtex":null,"citationCount":0,"paperId":"0193c417fa85fc544f5b01874c39647f0cff6447","pdfs":[],"title":"Procjena pouzdanosti DIAGNOdent ure\u0111aja za dijagnostiku okluzalnog karijesa"},{"bibtex":null,"citationCount":72,"paperId":"ae3716a5cf4781922d8d85e759ab19c7cf050bb2","pdfs":[],"title":"Visual and Tactile Assessment of Arrested Initial Enamel Carious Lesions: An in vivo Pilot Study"},{"bibtex":null,"citationCount":103,"paperId":"5bc01f60ef121d66d9963724c2d3800c5dd34989","pdfs":[],"title":"In vitro Comparison of Nyvad\u2019s System and ICDAS-II with Lesion Activity Assessment for Evaluation of Severity and Activity of Occlusal Caries Lesions in Primary Teeth"},{"bibtex":null,"citationCount":1,"paperId":"4cc9612f7ce9db8b324e3a77ff90f04a4115aa97","pdfs":[],"title":"Comparative Evaluation of ICDAS, WHO and Histological Examination in Detection of Occlusal Carious Lesions"},{"bibtex":null,"citationCount":27,"paperId":"c3b0718231a5d11e824a8456eb472712869d6d96","pdfs":[],"title":"Dental examiners consistency in applying the ICDAS criteria for a caries prevention community trial."},{"bibtex":null,"citationCount":0,"paperId":"b9a412fb89e58e8af4a217ced3fea5261a0422a9","pdfs":[],"title":"Validade preditiva de m\u00e9todos para a avalia\u00e7\u00e3o da atividade das les\u00f5es de c\u00e1rie em dentes dec\u00edduos"},{"bibtex":null,"citationCount":10,"paperId":"b46533ff18498ffdc33cdc7c9e4da0bb39c66084","pdfs":[],"title":"Radiographic pattern of underlying dentin lesions (ICDAS 4) in permanent teeth"},{"bibtex":null,"citationCount":11,"paperId":"3a03c37c0bd66e28bd6af05bfca2269268de87bc","pdfs":[],"title":"Do the ball-ended probe cause less damage than sharp explorers?\u2014An ultrastructural analysis"},{"bibtex":null,"citationCount":157,"paperId":"0dcfc94c3a84cae43b8cb9359a4a15c0d06d7a6f","pdfs":[],"title":"Diagnosis versus Detection of Caries"},{"bibtex":null,"citationCount":309,"paperId":"4f5adf74a2cad4ab6345b7b21a28e3cd64a52e43","pdfs":[],"title":"Detection and activity assessment of primary coronal caries lesions: a methodologic study."},{"bibtex":null,"citationCount":3,"paperId":"db31395895a09046586e4182de1eedd58e75646a","pdfs":[],"title":"The ICDAS system as a complementary method for the diagnosis of dental caries"},{"bibtex":null,"citationCount":0,"paperId":"86cd8eb93cca2fa270faedaeb0f9b0211b147e3e","pdfs":[],"title":"Performance of several diagnostic systems on detection of occlusal primary caries in permanent teeth"},{"bibtex":null,"citationCount":0,"paperId":"0bea2b2828848bf1c88a5d3a1429d06e045e1e95","pdfs":[],"title":"Review on International Caries Detection and Assessment System"},{"bibtex":null,"citationCount":227,"paperId":"8801b010adcab3dc63203c012308ae3f2be4fed1","pdfs":[],"title":"Construct and Predictive Validity of Clinical Caries Diagnostic Criteria Assessing Lesion Activity"},{"bibtex":null,"citationCount":0,"paperId":"094bc95a7516881dfc921f2ace8ad570872aac11","pdfs":[],"title":"Do combinations of clinical parameters related to caries activity status predict progression more accurately than individual parameters?"},{"bibtex":null,"citationCount":8,"paperId":"2b6451105b42659a3ec9f59d44c18860e85b2e23","pdfs":[],"title":"Use of the International Caries Detection and Assessment System by dental students at the University of Dammam, Saudi Arabia"},{"bibtex":null,"citationCount":12,"paperId":"5baab5b757c56cde8ae6552daad4619151e24204","pdfs":[],"title":"Current and future research in diagnostic criteria and evaluation of caries detection methods."},{"bibtex":null,"citationCount":2,"paperId":"12de2f633545bdd461de939eea1a3b147e278672","pdfs":[],"title":"Performance of Dental Undergraduate Students using International Caries Detection and Assessment system (ICDAS)"}],"scores":[0.9945170283317566,0.9938769936561584,0.9936580061912537,0.9936230182647705,0.9934089779853821,0.9932929873466492,0.9927510023117065,0.9922559857368469,0.9918959736824036,0.9918670058250427,0.9915689826011658,0.9915469884872437,0.9912160038948059,0.991212010383606,0.9908090233802795,0.9907829761505127,0.9907789826393127,0.99064701795578,0.9905930161476135,0.9905890226364136]},"s2_api":{"ids":["162ba32fc3d12a4d1707245b770f4a9d99350b23","49dbb04ddb197831a75e95f96d74152260d21192","594eb0c98fb833dfe92a1ebfef540af992e2426b","d2ceebf727119fb07228012c84f593d2b62ec3de","fcbb9da3df25a833d53af63aa12d06fc0b5bfe7f","628895e6e961b239ceb0b6764fab69c26b6ba818","a6e37611a1c2a97def65a9a5bfc57fc90cce6d9e","bb3d4feacad89d93bcb47e66de8b6e195b895b34","8f5c6899ee1d5b0825f23862082c168b92115c66","f5a9f2a6c392bb9f966992d4ab1f69f6fdebdaa0","d24b52f546987e97711d03681b8408ea8072c73e","04c1db0ac74316189b05cb4d7aef2e3bf19135a7","38890e238a74fd182b213707a73f8512241c594f","87654a0a5bf3baca9d5761786b376e0b39513977","9b7a08c5387f1f81a1ac3e5f5d50e5f87065c954","a02bce1269eb2584e95f0c30607f2a29231496b2","cd1b5415d6b2316c8bd2e6a30f318ea90900505f","b72fd2c07fbe58c64377d59ceef53d5c2bbb1770","008ebf1fc4d35e2bd5f3c30e86f8f2455e7993d2","126235da89ab7089eead15ed5c36153bf89eeb2e"],"papers":[{"bibtex":null,"citationCount":26,"paperId":"162ba32fc3d12a4d1707245b770f4a9d99350b23","pdfs":[],"title":"Core Outcomes Measures in Dental Computer Vision Studies (DentalCOMS)."},{"bibtex":null,"citationCount":1,"paperId":"49dbb04ddb197831a75e95f96d74152260d21192","pdfs":[],"title":"Longitudinal Assessment of an AI-Based Software for Interproximal Caries Detection in Bitewing Radiographs."},{"bibtex":null,"citationCount":1,"paperId":"594eb0c98fb833dfe92a1ebfef540af992e2426b","pdfs":[],"title":"DIAGNOSTIC ACCURACY OF AI-BASED VERSUS CONVENTIONAL RADIOGRAPHIC CARIES DETECTION IN PEDIATRIC PATIENTS: A CROSS-SECTIONAL STUDY"},{"bibtex":null,"citationCount":0,"paperId":"d2ceebf727119fb07228012c84f593d2b62ec3de","pdfs":[],"title":"Rethinking diagnostic performance metrics in imaging AI: lessons from caries detection on radiographs"},{"bibtex":null,"citationCount":31,"paperId":"fcbb9da3df25a833d53af63aa12d06fc0b5bfe7f","pdfs":[],"title":"Diagnostic performance of artificial intelligence-aided caries detection on bitewing radiographs: a systematic review and meta-analysis"},{"bibtex":null,"citationCount":1,"paperId":"628895e6e961b239ceb0b6764fab69c26b6ba818","pdfs":[],"title":"Correction to: Assessment of YOLOv3 for caries detection in bitewing radiographs based on the ICCMS\u2122 radiographic scoring system"},{"bibtex":null,"citationCount":2,"paperId":"a6e37611a1c2a97def65a9a5bfc57fc90cce6d9e","pdfs":[],"title":"Accuracy of deep learning-based AI models for early caries lesion detection: the influence of annotation quality and reference choice"},{"bibtex":null,"citationCount":29,"paperId":"bb3d4feacad89d93bcb47e66de8b6e195b895b34","pdfs":[],"title":"Comparison of artificial intelligence vs. junior dentists\u2019 diagnostic performance based on caries and periapical infection detection on panoramic images"},{"bibtex":null,"citationCount":10,"paperId":"8f5c6899ee1d5b0825f23862082c168b92115c66","pdfs":[],"title":"Developing the Benchmark: Establishing a Gold Standard for the Evaluation of AI Caries Diagnostics"},{"bibtex":null,"citationCount":2,"paperId":"f5a9f2a6c392bb9f966992d4ab1f69f6fdebdaa0","pdfs":[],"title":"Development and evaluation of an artificial intelligence (AI) model for detecting dental caries from 3D intraoral scans."},{"bibtex":null,"citationCount":0,"paperId":"d24b52f546987e97711d03681b8408ea8072c73e","pdfs":[],"title":"AI-Based Clinical Decision Support Systems for Secondary Caries on Bitewings: A Multi-Algorithm Comparison"},{"bibtex":null,"citationCount":4,"paperId":"04c1db0ac74316189b05cb4d7aef2e3bf19135a7","pdfs":[],"title":"Introducing a Dental Caries Marking Software and Evaluate Radiologists\u2019 Disagreement in Caries Detection Using this Software"},{"bibtex":null,"citationCount":0,"paperId":"38890e238a74fd182b213707a73f8512241c594f","pdfs":[],"title":"Emerging trends in the early diagnosis of dental caries: a scoping review of artificial intelligence, digital diagnostics, and teledentistry."},{"bibtex":null,"citationCount":5,"paperId":"87654a0a5bf3baca9d5761786b376e0b39513977","pdfs":[],"title":"Caries Detection and Classification in Photographs Using an Artificial Intelligence-Based Model\u2014An External Validation Study"},{"bibtex":null,"citationCount":12,"paperId":"9b7a08c5387f1f81a1ac3e5f5d50e5f87065c954","pdfs":[],"title":"Validation of an Artificial Intelligence-Based Model for Early Childhood Caries Detection in Dental Photographs"},{"bibtex":null,"citationCount":0,"paperId":"a02bce1269eb2584e95f0c30607f2a29231496b2","pdfs":[],"title":"Current Trends in Modern Dentistry: Diagnostic Sensitivity of AI in Detecting Dental Conditions. A Systematic Review and Meta-Analysis"},{"bibtex":null,"citationCount":2,"paperId":"cd1b5415d6b2316c8bd2e6a30f318ea90900505f","pdfs":[],"title":"Diagnostic efficiency of digital photography and AI-assisted image interpretation in dental caries examination: An umbrella review."},{"bibtex":null,"citationCount":0,"paperId":"b72fd2c07fbe58c64377d59ceef53d5c2bbb1770","pdfs":[],"title":"DIAGNOSTIC PERFORMANCE OF MACHINE LEARNING-AIDED PROXIMAL CARIES DETECTION: A SYSTEMATIC REVIEW AND META-ANALYSIS."},{"bibtex":null,"citationCount":0,"paperId":"008ebf1fc4d35e2bd5f3c30e86f8f2455e7993d2","pdfs":[],"title":"Precision and Accessibility in Periodontal Diagnosis: A Comparative Study of AI and Clinical Expertise"},{"bibtex":null,"citationCount":10,"paperId":"126235da89ab7089eead15ed5c36153bf89eeb2e","pdfs":[],"title":"Artificial Intelligence in Detecting Periodontal Disease From Intraoral Photographs: A Systematic Review"}],"scores":[]}},"time":5.361314535140991}
