{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T15:28:37Z","timestamp":1788449317901,"version":"build-2803163510"},"reference-count":21,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aap.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Periodontology"],"published-print":{"date-parts":[[2026,4]]},"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n The purpose of this study is to report on the development of an artificial intelligence (AI) model designed to improve compliance in periodontal maintenance patients.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n Fifty adult patients (32 females and 18 males; aged 25 to 78 years) with diagnosis and treatment of Generalized or Localized Periodontitis stages I, II, or III; grades A\u2013C who were following a 3\u2010month periodontal maintenance interval were provided an AI\u2010based smartphone application (app) that provided personalized educational, motivational, and risk\u2010awareness information every week between maintenance visits. Recession (REC), probing pocket depth (PPD), clinical attachment level (CAL), plaque index (PI), bleeding on probing (BOP), and gingival index (GI) captured at each maintenance visit out to 6 months were compared with baseline. In\u2010office interviews were conducted to assess subjective data points, and cognitive interviews were conducted to validate patient\u2010reported outcomes (PRO).<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n REC, PPD, and CAL remained stable through all timepoints. PI, BOP, and GI demonstrated significant improvement compared with baseline (\n p<\/jats:italic>\n \u00a0<\u00a00.01). PRO were validated and revealed that most subjects found the app to be easy to use, desired more interaction, perceived it as educational by raising their awareness of their oral hygiene, and would recommend the use of the app to a friend.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n An AI\u2010based smartphone application was trained on a private practice maintenance population of three periodontists. The subjects demonstrated improvements in PI, BOP, and GI with no changes in REC, PPD, or CAL. Patients found the app to be educational and beneficial by improving their understanding of their periodontal disease risk.<\/jats:p>\n <\/jats:sec>\n \n Plain language summary<\/jats:title>\n An artificial intelligence model (AI) was developed to improve periodontal maintenance compliance. Compliance with periodontal maintenance in patients decreases dramatically after 1 year. This is a proof\u2010of\u2010concept study using an AI\u2010based smartphone application (app) that communicates individualized periodontal disease risk awareness messages that were educational and motivational to effect a behavioral change in hopes of improving compliance. Measurements of disease stability\/instability, such as gum inflammation, bleeding, bone loss, and assessment of brushing effectiveness, were captured at baseline and at subsequent office visits every 3 months for a total of 6 months. Subjective patient information was captured via in\u2010office interviews to supplement clinical data and provide the AI model with multimodal data points. Patient\u2010reported outcome surveys were developed via cognitive interviews. Results showed improvements in brushing effectiveness, which translated to less gum bleeding and inflammation. Other clinical measurements of disease activity showed no change, which could translate to a lack of disease progression. Patient\u2010reported outcome development revealed that most of the subjects found the interaction with the app to be positive and beneficial. This proof\u2010of\u2010concept study demonstrates a novel approach using an AI\u2010based smartphone app to be worthy of further investigation on efficacy and possibly defines an objective measure of patient compliance.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jper.25-0037","type":"journal-article","created":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T11:57:17Z","timestamp":1771502237000},"page":"771-781","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Development of an artificial intelligence platform to improve compliance in periodontal maintenance patients: A proof\u2010of\u2010concept study"],"prefix":"10.1002","volume":"97","author":[{"given":"Takanari","family":"Miyamoto","sequence":"first","affiliation":[{"name":"Private Practice La Vista Nebraska USA"},{"name":"Department of Periodontics Creighton University School of Dentistry Omaha Nebraska USA"},{"name":"McGuire Institute Study Private Practice\u2010Based Clinical Research Network Houston Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"McGuire","sequence":"additional","affiliation":[{"name":"McGuire Institute Study Private Practice\u2010Based Clinical Research Network Houston Texas USA"},{"name":"Private Practice Houston Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. 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