Results 211 to 220 of about 72,858 (297)

Comparative analysis of artificial intelligence tools in generating diabetic retinopathy guidelines. [PDF]

Adv Ophthalmol Pract Res
Cao F, Hou S.
europepmc   +1 more source

John Logan: A Retrospective [PDF]

, 1981
Soldofsky, Alan
core   +1 more source

Synthesizing beaver coexistence messaging with the capability, opportunity, and motivation behavior model

Conservation Biology, EarlyView.
Abstract In the western United States, conservation practitioners are increasingly working with private landowners to restore habitat for North American beavers (Castor canadensis) and to use nonlethal mitigation techniques when beavers damage crops and infrastructure.
Brian D. Erickson, Megan S. Jones
wiley   +1 more source

Machine learning-based prediction of diabetic retinopathy from pupillary abnormalities in a South Indian population. [PDF]

PLoS One
Surya J, Tamilselvi S, Roy M, Chinnasamy S, Raman R, Suchetha M, Rajendran G.   +6 more
europepmc   +1 more source

Fluctuations in angle lambda with the pupil diameter and correlations with biometric values in a healthy population. [PDF]

Ophthalmic Physiol Opt
Rateaux M, Vienne-Jumeau A, Bremond-Gignac D, Robert MP.   +3 more
europepmc   +1 more source

Capturing Optimal Mobile 2D Facial Images in Remote Aesthetics Medicine Clinical Trials: Technical Considerations for Facial Severity Analysis. [PDF]

JMIR Form Res
Caiazza D, Kreutzkamp S.
europepmc   +1 more source

Guidelines for preoperative visual function and imaging examination standards in vitreoretinal surgery (2025). [PDF]

Int J Ophthalmol
Shao Y, Ma J, Wang ZY, Expert Workgroup of Guidelines for Preoperative Visual Function and Imaging Examination Standards in Vitreoretinal Surgery (2025), Ophthalmic Imaging and Intelligent Medicine Branch Chinese Medicine Education Association; Ophthalmology Committee of International Association of Translational Medicine; Ophthalmology Committee of International Association of Intelligent Medicine.   +4 more
europepmc   +1 more source

Placing anurans in water can improve photo-based individual identification. [PDF]

PLoS One
Nemesházi E, Mikó Z, Ujhegyi N, Kásler A, Lehofer N, Bókony V.   +5 more
europepmc   +1 more source

Accuracy of ChatGPT, Gemini, Claude and DeepSeek in Carbohydrate Counting

Diabetes, Obesity and Metabolism, EarlyView.
ABSTRACT Aims To evaluate the accuracy of four general‐purpose artificial intelligence (AI) models—ChatGPT (OpenAI), Gemini (Google), Claude (Anthropic) and DeepSeek (DeepSeek AI)—in calculating the carbohydrate content of meals compared with clinicians‐calculated reference values.
Luca Zagaroli, Nicholas Caione, Sabina Zara, Federica Guerra, Antonella Zugaro, Marco Giorgio Baroni, Maria Laura Iezzi, Maurizio Delvecchio   +7 more
wiley   +1 more source

Picture quality between DSLR cameras and smartphone cameras among prosthodontics postgraduate students. [PDF]

Bioinformation
Mangtani V, Tripathi A, Gupta A, Soni M, Chansoria H, Gupta S.   +5 more
europepmc   +1 more source