{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T09:36:45Z","timestamp":1793007405865,"version":"4.5.0"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T00:00:00Z","timestamp":1792108800000},"content-version":"vor","delay-in-days":15,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100015150","name":"St. Michael's Hospital Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100015150","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004319","name":"Pfizer","doi-asserted-by":"publisher","award":["70357135"],"award-info":[{"award-number":["70357135"]}],"id":[{"id":"10.13039\/100004319","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Machine-learning models can distinguish acromegaly from controls in single photographs, but whether gradual facial change can be measured within the same person from ordinary photographs is unknown. We tested whether a person's face shifts measurably toward an acromegaly-associated pattern over time.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Multicenter, international, cross-sectional cohort study with within-subject longitudinal analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>People with acromegaly and other pituitary neuroendocrine tumours contributed retrospective photographs. Two timepoints per person were paired by self-reported disease stage when available, with chronological pairing otherwise. A face-recognition model and a general-image model described each image, and leave-one-patient-out scoring quantified within-person movement toward the acromegaly-associated pattern.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Of 582 participants, 110 contributed usable frontal photographs and 69 had 2 timepoints (50 acromegaly, 19 tumour controls). The facial score separated held-out advanced disease from control faces (AUC 0.858). In acromegaly, the median within-person shift was 0.59 and 76.0% moved in the predicted direction (P = .0003); 81.5% of clean untreated pairs moved as predicted (P = .0008). The 3 contrast strata ordered directionally, although the trend was not significant (P = .15). The 15 non-Cushing aging controls showed no significant shift (P = .72), and the between-group difference remained after adjustment for photograph interval (P = .029). Prediagnosis untreated baselines showed modest separation from all control baselines (AUC 0.65, 1-sided P = .033). The general-image model showed no within-person change (P = .32).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Acromegaly-associated facial change is measurable within individuals from ordinary photographs, supporting further evaluation of longitudinal photograph-based monitoring and earlier recognition.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/ejendo\/lvag189","type":"journal-article","created":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T11:50:37Z","timestamp":1792065037000},"page":"625-634","source":"Crossref","is-referenced-by-count":0,"title":["Machine learning quantifies within-subject facial change in acromegaly"],"prefix":"10.1093","volume":"195","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-1262-2154","authenticated-orcid":false,"given":"Ali","family":"Ammar","sequence":"first","affiliation":[{"name":"Division of Neurosurgery, St. 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