https://www.selleckchem.com/products/azd5305.html 08 per 10 µm increase in TCT; p<0.001), (HR 1.03 per 1D increase; p=0.02) and (HR 0.98 per year younger; p=0.01), respectively. Steeper Max-K and younger age were the most clinically useful baseline predictors of progression as they were associated with worsening of two clinical parameters. Every 1D steeper Max-K was associated with a 7% and 3% greater risk of worsening VA and thinning TCT, respectively. Each 1 year younger was associated with a 4% and 2% greater risk of steepening Max-K and thinning TCT, respectively. Steeper Max-K and younger age were the most clinically useful baseline predictors of progression as they were associated with worsening of two clinical parameters. Every 1D steeper Max-K was associated with a 7% and 3% greater risk of worsening VA and thinning TCT, respectively. Each 1 year younger was associated with a 4% and 2% greater risk of steepening Max-K and thinning TCT, respectively. To explore and evaluate an appropriate deep learning system (DLS) for the detection of 12 major fundus diseases using colour fundus photography. Diagnostic performance of a DLS was tested on the detection of normal fundus and 12 major fundus diseases including referable diabetic retinopathy, pathologic myopic retinal degeneration, retinal vein occlusion, retinitis pigmentosa, retinal detachment, wet and dry age-related macular degeneration, epiretinal membrane, macula hole, possible glaucomatous optic neuropathy, papilledema and optic nerve atrophy. The DLS was developed with 56 738 images and tested with 8176 images from one internal test set and two external test sets. The comparison with human doctors was also conducted. The area under the receiver operating characteristic curves of the DLS on the internal test set and the two external test sets were 0.950 (95% CI 0.942 to 0.957) to 0.996 (95% CI 0.994 to 0.998), 0.931 (95% CI 0.923 to 0.939) to 1.000 (95% CI 0.999 to 1.000) and 0.934 (95% CI 0.929 to 0.938) t