{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T14:21:45Z","timestamp":1787840505751,"version":"build-2784847793"},"reference-count":7,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"Suppl 2","license":[{"start":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T00:00:00Z","timestamp":1748736000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-sa\/4.0"}],"content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6]]},"abstract":"<jats:title>\n                    A\n                    <jats:sc>BSTRACT<\/jats:sc>\n                  <\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>This study evaluated AI-based analysis of dental periapical lesions using CBCT scans, conducted at the Department of Oral Medicine and Radiology, New Horizon Dental College, Bilaspur, Chhattisgarh.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method:<\/jats:title>\n                    <jats:p>A total of 500 CBCT scans were analyzed, with 400 scans used to train AI software and 100 scans assessed by two radiologists to test the software\u2019s performance. The AI classified lesions into periapical cysts, abscesses, or granulomas. Sensitivity, specificity, and accuracy were calculated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Result:<\/jats:title>\n                    <jats:p>\n                      Cysts were the largest lesions, with regular margins (99.09%) and significant cortical expansion (93.36%), causing teeth displacement (66.36%). Abscesses and granulomas predominantly affected the maxilla, showing moderate hypodensity (100%) with minimal structural changes. Radiologists achieved perfect agreement (0.98,\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      &lt; .001) in 77% of scans. Manual machine learning AI achieved 100% accuracy, while deep learning AI demonstrated 84.62% accuracy, with moderate to substantial agreement for lesion dimensions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>Manual machine learning AI showed superior accuracy compared to deep learning AI, demonstrating its potential for radiographic diagnosis of periapical lesions.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.4103\/jpbs.jpbs_2002_24","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T01:02:46Z","timestamp":1750208566000},"page":"S1475-S1477","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of Artificial Intelligent Systems Based Analysis in Dental Periapical Lesions \u2013 A Radiological Study"],"prefix":"10.4103","volume":"17","author":[{"given":"Giridhar","family":"Naidu","sequence":"first","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramanpal Singh","family":"Makkad","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fiza","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pallavi","family":"Sinha","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Swatantra","family":"Shrivastava","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Narayan Prasad","family":"Tripathi","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dasharathraj K.","family":"Shetty","sequence":"additional","affiliation":[{"name":"Department of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, (Deemed to be University u\/s 3 of the UGC Act 1956), Manipal, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarthak","family":"Shastri","sequence":"additional","affiliation":[{"name":"Department of Information and Communications Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ankita","family":"Shrivastava","sequence":"additional","affiliation":[{"name":"Department of Oral Medicine and Radiology, New Horizon Dental College and Research Institute Sakri, Bilaspur, Chhattisgarh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"R1-20250618","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s00330-018-5644-3","article-title":"Artificial intelligence in radiology:How will be affected?","volume":"29","author":"Wong","year":"2019","journal-title":"Eur 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periapical radiography and cone-beam computed tomography scans in diagnosing apical periodontitis using histopathological findings as a gold standard","volume":"35","author":"de Paula-Silva","year":"2009","journal-title":"J Endod"},{"key":"R6-20250618","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1016\/j.joen.2009.11.005","article-title":"Evaluation of pathologists (histopathology) and radiologists (cone beam computed tomography) differentiating radicular cysts from granulomas","volume":"36","author":"Rosenberg","year":"2010","journal-title":"J Endod"},{"key":"R7-20250618","doi-asserted-by":"crossref","first-page":"833","DOI":"10.1016\/j.joen.2006.03.008","article-title":"Differential diagnosis of large periapical lesions using cone-beam computed tomography measurements and biopsy","volume":"32","author":"Simon","year":"2006","journal-title":"J Endod"}],"container-title":["Journal of Pharmacy and Bioallied Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.ovid.com\/10.4103\/jpbs.jpbs_2002_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,27]],"date-time":"2026-08-27T13:24:05Z","timestamp":1787837045000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ovid.com\/10.4103\/jpbs.jpbs_2002_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6]]},"references-count":7,"journal-issue":{"issue":"Suppl 2","published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.4103\/jpbs.jpbs_2002_24","relation":{},"ISSN":["0976-4879","0975-7406"],"issn-type":[{"value":"0976-4879","type":"print"},{"value":"0975-7406","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6]]},"assertion":[{"value":"2024-12-28","name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-02-09","name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}}]}}