Ranks distinct AI gain and problem claims from the published record. Scores reward impact, independent source strength, scale, confidence, and recency.
In a prospective cohort of 33 ICU patients with acute brain injury, investigators tested whether bedside functional near-infrared spectroscopy during passive audio movie listening could support early prognostication. Using functional connectivity features to train a machine learning model, they classified 6-month functional outcome defined by Glasgow Outcome Scale-Extended.
A systematic review and meta-analysis to February 9, 2025, evaluated artificial intelligence for diabetic retinopathy assessment using ultra-widefield color fundus images, which capture a larger retinal area without pupil dilation. Of 527 records, 17 studies were reviewed and four were meta-analyzed, all using Optos software, to estimate sensitivity and specificity for AI-driven screening.
A diagnostic accuracy study published July 24, 2026 developed an interpretable deep learning framework to distinguish vitiligo from postinflammatory hypopigmentation, two conditions with similar depigmented lesions. Using 332 clinical images from King Abdullah University Hospital and public sources, a fine-tuned MobileNetV2 was evaluated with patient-wise 5-fold cross-validation.
By September 2026, a scoping review of literature up to June 2025 synthesized 15 studies on augmented and mixed reality as auxiliary tools in dentistry and their integration with AI. Most evidence was in implant dentistry, where MR-based dynamic navigation achieved sub-millimetric accuracy and outperformed freehand technique, with reported improvements in angular accuracy for inexperienced operators and more conservative tissue removal in endodontics and tooth preparation.
Researchers reviewed the state of AI in healthcare, noting rapid acceleration of research and demonstrations across medical domains but few cases where techniques have moved into routine clinical use. The article frames translation as the central issue and outlines categories of obstacles that prevent research models from reaching practice.
From October 5 to 11, 2025, researchers tested five large language models on 20 pulmonary tuberculosis questions spanning five themes, generating 100 responses and rating them with C-PEMAT-P, GQS, and seven readability measures. GPT-5 ranked highest on C-PEMAT-P followed by Doubao, GQS was similar across models, and models differed significantly on several readability indices.
Published 12 February 2026 in Societies, this peer-reviewed article analyzes how algorithmic systems in employment screening, welfare administration, and digital platforms function as social and institutional actors. Using regulatory materials, platform governance documents, technical disclosures, and composite vignettes synthesized from public evidence, it examines how automated classification and delegated authority reshape how individuals are evaluated and legitimised.
By April 13 2026, researchers reported results from 21 semi-structured interviews with local journalists in Germany examining use of data and AI, challenges in interaction, and perceived opportunities for AI-supported reporting systems.
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