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https://www.selleckchem.com/products/dotap-chloride.html 05). Further risk factors for FSD were identified as neutral and dissatisfied marital relations, lower educational level and smoking (  < .05). We report a clear association between deteriorating sexual function and increasing STRAW + 10 classification, suggesting the consequence of decreasing ovarian function. HRT containing 'natural hormones' was shown to have a beneficial effect on FSD. The results are reported here for the first time in Chinese women. We report a clear association between deteriorating sexual function and increasing STRAW + 10 classification, suggesting the consequence of decreasing ovarian function. HRT containing 'natural hormones' was shown to have a beneficial effect on FSD. The results are reported here for the first time in Chinese women.Background Over the next 25 years, the global prevalence of diabetes is expected to grow to affect 700 million individuals. Consequently, an unprecedented number of patients will be at risk for vision loss from diabetic eye disease. This demand will almost certainly exceed the supply of eye care professionals to individually evaluate each patient on an annual basis, signaling the need for 21st century tools to assist our profession in meeting this challenge. Methods Review of available literature on artificial intelligence (AI) as applied to diabetic retinopathy (DR) detection and predictionResults The field of AI has seen exponential growth in evaluating fundus photographs for DR. AI systems employ machine learning and artificial neural networks to teach themselves how to grade DR from libraries of tens of thousands of images and may be able to predict future DR progression based on baseline fundus photographs. Conclusions AI algorithms are highly promising for the purposes of DR detection and will likely be able to reliably predict DR worsening in the future. A deeper understanding of these systems and how they interpret images is critical as they

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