{"id":567607,"date":"2026-07-25T14:08:23","date_gmt":"2026-07-25T14:08:23","guid":{"rendered":"https:\/\/www.newsbeep.com\/ie\/567607\/"},"modified":"2026-07-25T14:08:23","modified_gmt":"2026-07-25T14:08:23","slug":"ocular-biomarkers-for-adhd-classification-emj","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/ie\/567607\/","title":{"rendered":"Ocular Biomarkers for ADHD Classification \u2013 EMJ"},"content":{"rendered":"

ADHD CLASSIFICATION using brainstem-based\u00a0ocular<\/a>\u00a0biomarkers\u00a0demonstrated\u00a0promising diagnostic performance in children and adults,\u00a0according to a new multicentre study.\u00a0<\/p>\n

Current\u00a0attention deficit hyperactivity disorder<\/a>\u00a0(ADHD)\u00a0assessment often relies on clinical history, rating scales, and performance testing, all of which can be influenced by subjective interpretation.\u00a0<\/p>\n

To address this challenge, investigators developed a machine learning framework that analysed task-evoked pupil diameter and binocular eye movement synchrony during a visual attention task.\u00a0<\/p>\n

Brainstem Biomarkers and ADHD Classification\u00a0<\/p>\n

Researchers evaluated 439 participants recruited from 14 clinical centres across Spain and the UK, including 324 children and 115 adults.\u00a0\u00a0<\/p>\n

Researchers classified participants as\u00a0either\u00a0healthy, with ADHD, or uncertain.\u00a0<\/p>\n

The study generated two outputs, a diagnostic score and an impulsivity score, by combining information from independent models assessing pupil dynamics and eye movement synchrony.\u00a0\u00a0<\/p>\n

In the paediatric cohort, selective classification achieved sensitivity and specificity values of 0.79 and 0.82 respectively for the diagnostic score.\u00a0<\/p>\n

The impulsivity score achieved sensitivity and specificity values of 0.74 and 0.70.\u00a0\u00a0<\/p>\n

By deferring uncertain cases, overall diagnostic reliability improved compared with standard binary classification.\u00a0\u00a0<\/p>\n

Validation Across Paediatric and Adult Cohorts\u00a0<\/p>\n

The researchers then evaluated performance in an independent adult cohort to assess cross-population generalisability.\u00a0\u00a0<\/p>\n

Despite expected differences between paediatric and adult populations, the diagnostic score\u00a0retained\u00a0discriminative capability.\u00a0\u00a0<\/p>\n

Under selective classification, the diagnostic score achieved sensitivity of 0.66 and specificity of 0.86, while the impulsivity score reached sensitivity of 0.68 and specificity of 0.92.\u00a0\u00a0<\/p>\n

These findings\u00a0indicated\u00a0that the ocular biomarkers remained informative beyond the population used for model development.\u00a0\u00a0<\/p>\n

The approach also\u00a0maintained\u00a0practical feasibility, with complete diagnostic predictions generated in approximately 20 seconds per participant.\u00a0\u00a0<\/p>\n

Explainable AI Revealed Key Ocular Signals\u00a0<\/p>\n

Explainability analyses provided insight into the physiological features driving model performance.\u00a0\u00a0<\/p>\n

Attention weighting showed that trials associated with increasing pupil diameter after cue presentation contributed most strongly to classification decisions.\u00a0\u00a0<\/p>\n

Saliency analyses further\u00a0identified\u00a0periods\u00a0immediately\u00a0following cue-onset and stimulus-onset as the most influential temporal windows.\u00a0<\/p>\n

The authors projected that combining the biomarker with standard rating scales could theoretically enhance clinical pathways.\u00a0\u00a0<\/p>\n

Under a screening approach, combined sensitivity was estimated at 95%, while a confirmation strategy was projected to achieve specificity of 96%.\u00a0\u00a0<\/p>\n

The researchers concluded that objective ocular biomarkers may help support ADHD classification, improve diagnostic consistency, and optimise use of specialist assessment resources.\u00a0<\/p>\n

Reference\u00a0<\/p>\n

Ranathunga C\u00a0et al. Real-world clinical validation of brainstem-based ocular biomarkers for ADHD classification in children and adults. Sci Rep.\u00a02026;DOI:10.1038\/s41598-026-56036-0\u00a0<\/p>\n

Featured\u00a0image:\u00a0Mahachoke\u00a04289-6395\u00a0on\u00a0Adobe Stock\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"ADHD CLASSIFICATION using brainstem-based\u00a0ocular\u00a0biomarkers\u00a0demonstrated\u00a0promising diagnostic performance in children and adults,\u00a0according to a new multicentre study.\u00a0 Current\u00a0attention deficit hyperactivity…\n","protected":false},"author":2,"featured_media":567608,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[103,61,60],"class_list":["post-567607","post","type-post","status-publish","format-standard","has-post-thumbnail","category-health","tag-health","tag-ie","tag-ireland"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/567607","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/comments?post=567607"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/posts\/567607\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media\/567608"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/media?parent=567607"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/categories?post=567607"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/ie\/wp-json\/wp\/v2\/tags?post=567607"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}