{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,3]],"date-time":"2026-09-03T05:16:37Z","timestamp":1788412597551,"version":"build-2803163510"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science and Technology Council","award":["NSTC 115-2314-B-038-057"],"award-info":[{"award-number":["NSTC 115-2314-B-038-057"]}]},{"award":["NSTC 115-2314-B-038-057"],"award-info":[{"award-number":["NSTC 115-2314-B-038-057"]}],"id":[{"id":"https:\/\/ror.org\/02kv4zf79","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Background: Predictive performance does not establish whether model-identified risks correspond to feasible, equitable pathways. We assessed the actionability and equity of a severe tooth loss prediction model using constrained algorithmic recourse and same-source temporal validation. Methods: An Explainable Boosting Machine was trained using 2022 Behavioral Risk Factor Surveillance System data from 433,772 adults. High-risk adults underwent recourse auditing incorporating immutability locks, behavioral directionality, physiological safety floors, and at most three feature changes. Recourse represented hypothetical movement within model space, not treatment advice, causal risk reduction, or reversal of tooth loss. Primary reachability was the unweighted analytic-cohort proportion for which the frozen engine identified a feasible pathway; a BRFSS survey-weighted domain sensitivity analysis used final weights, strata, and primary sampling units. The audit separated reachability from conditional burden among reachable adults. Equity was evaluated across Social Indicators of Disparity Index (SIDI) and income strata using Oaxaca\u2013Blinder decomposition. The frozen specification was evaluated in a 2022 holdout and the 2024 BRFSS cohort (N = 448,213) without retraining. Results: Survey-weighted areas under the receiver operating characteristic curve were 0.858, 0.855, and 0.858 in the 2022 full, 2022 holdout, and 2024 cohorts. Primary unweighted reachability was 10.61%, 10.54%, and 9.82%; corresponding survey-weighted estimates were 12.69% (95% design-aware CI, 12.33\u201313.07%), 12.31% (11.54\u201313.12%), and 11.30% (10.95\u201311.65%), respectively. Thus, reachability remained limited under both estimands. The high-SIDI group showed poorer calibration. Under the prespecified primary SIDI-neutral additive-cost specification, residual conditional cost differences across SIDI strata were small; alternative burden metrics were direction-dependent. The income residual attenuated from the 2022 holdout to 2024, although its confidence intervals were fixed-pipeline row-bootstrap intervals rather than fully design-based intervals. Conclusions: Stable predictive performance masked limited model-space actionability. Integrating explicitly labeled reachability estimands, conditional burden, equity, and temporal transport can strengthen pre-deployment evaluation. Because severe tooth loss is irreversible, recourse pathways should be interpreted as a stress test of model-implied modifiable factors rather than evidence of reversibility.<\/jats:p>","DOI":"10.3390\/bioengineering13091020","type":"journal-article","created":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T08:31:13Z","timestamp":1788251473000},"page":"1020","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Pre-Deployment Audit of Actionability and Equity in Severe Tooth Loss Prediction Using Constrained Algorithmic Recourse and Temporal Validation"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-5305-2266","authenticated-orcid":false,"given":"Quang Tuan","family":"Lam","sequence":"first","affiliation":[{"name":"School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"},{"name":"AIBioMed Research Group, Taipei Medical University, Taipei 11031, Taiwan"},{"name":"Faculty of Odonto-Stomatology, Da Nang University of Medical Technology and Pharmacy, Da Nang 550000, Vietnam"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5176-4102","authenticated-orcid":false,"given":"Fang-Yu","family":"Fan","sequence":"additional","affiliation":[{"name":"School of Dental Technology, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7168-9429","authenticated-orcid":false,"given":"Tzu-Yu","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6637-7044","authenticated-orcid":false,"given":"Sheng-Wei","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"given":"Cathy Chia-Yu","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Life Sciences, National Central University, Taoyuan City 32001, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7013-2979","authenticated-orcid":false,"given":"Tong-Hsien","family":"Chow","sequence":"additional","affiliation":[{"name":"Department of Sports Science, R.O.C. Military Academy, Kaohsiung 83059, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7728-1539","authenticated-orcid":false,"given":"Minh Huu Nhat","family":"Le","sequence":"additional","affiliation":[{"name":"Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, Yale University, New Haven, CT 06520, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1159-6973","authenticated-orcid":false,"given":"Giang","family":"Vu","sequence":"additional","affiliation":[{"name":"School of Global Health Management and Informatics, University of Central Florida, Orlando, FL 32801, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"software","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0633-8913","authenticated-orcid":false,"given":"Yung-Li","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4896-7926","authenticated-orcid":false,"given":"Nguyen Quoc Khanh","family":"Le","sequence":"additional","affiliation":[{"name":"AIBioMed Research Group, Taipei Medical University, Taipei 11031, Taiwan"},{"name":"Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 11031, Taiwan"},{"name":"Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8451-0280","authenticated-orcid":false,"given":"I-Ta","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Dentistry, College of Oral Medicine, Taipei Medical University, Taipei 11031, Taiwan"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"866","DOI":"10.7326\/M18-1990","article-title":"Ensuring fairness in machine learning to advance health equity","volume":"169","author":"Rajkomar","year":"2018","journal-title":"Ann. 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