Diabetes Prediction Using Artificial Neural Network

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3

Meeting the challenge of diabetes in ageing and diverse populations: a review of the literature from the UK

The impact of type 2 diabetes on ageing societies is great and populations across the globe are becoming more diverse. Complications of diabetes unequally affect particular groups in the UK older people, and people with a South Asian background are two population groups with increased risk whose numbers will grow in the future. We explored the evidence about diabetes care for older people with South Asian ethnicity to understand the contexts and mechanisms behind interventions to reduce inequalities. We used a realist approach to review the literature, mapped the main areas where relevant evidence exists, and explored the concepts and mechanisms which underpinned interventions. From this we constructed a theoretical framework for a programme of research and put forward suggestions for what our analysis might mean to providers, researchers, and policy makers. Broad themes of cultural competency; comorbidities and stratification; and access emerged as mid-level mechanisms which have individualised, culturally intelligent, and ethical care at their heart and through which inequalities can be addressed. These provide a theoretical framework for future research to advance knowledge about concordance; culturally meaningful measures of depression and cognitive impairment; and care planning in different contexts which support effective diabetes care for aging and diverse populations

Exploring Resilience When Living with a Wound — An Integrative Literature Review

The psychological impact for patients with wounds can be significant, and adverse psychological effects frequently occur when there are permanent changes in the body’s structure or function. Evidence suggests that anxiety, depression and stress can adversely affect the wound healing process. An integrative review examined any paper that discussed any patient in any health care setting who had experienced a psychological impact from the experience of having a wound and the experience of being resilient in that context. Ninety nine papers were located in the initial search with twelve meeting the inclusion criteria and being reviewed. A review of the papers identified that improvement and maintenance of quality of life was perceived to be an important aspect of patient management, but none focused on resilience as a primary endpoint. Further research is required into the clinical benefits of resilient behaviours in patients living with a wound