PURPOSE: Differentiating the underlying pathology of macular edema in patients with diabetic retinopathy following cataract surgery can be challenging. In 2015, Munk and colleagues trained and tested a machine learning classifier which uses optical c...
PURPOSE: In diabetic patients presenting with macular edema (ME) shortly after cataract surgery, identifying the underlying pathology can be challenging and influence management. Our aim was to develop a simple clinical classifier able to confirm a d...
Journal of cataract and refractive surgery
38529959
PURPOSE: To use a combination of partial least squares regression and a machine learning approach to predict intraocular lens (IOL) tilt using preoperative biometry data.
OBJECTIVES: To analyse the accuracy of artificial intelligence (AI)-driven intraocular (IOL) calculation formulae, together with established formulae using the heteroscedastic methodology and the Eyetemis Analysis Tool.