In recent years, retinal disorders have grown to be a serious public health issue. Retinopathy of Prematurity (ROP) and Diabetic Retinopathy (DR) are the foremost factors of vision impairments in children and youngsters correspondingly. These illnesses develop gradually and have no visible symptoms. To avoid vision damage, it is crucial to identify these conditions quickly and receive the appropriate medication. Therefore, a completely automated approach for identifying retinal disorders is needed. It is designed to reduce human contact for the identification of Diabetic Retinopathy (DR) and Retinopathy of Prematurity (ROP) while maintaining the excellent accuracy of the classification. This paper presents an enhanced deep learning model LeNet-5 for retinal disease categorization framework. To achieve the desired findings, the DeepLabv3+ based blood vessel segmentation is carried out. After segmenting the retinal vessels, the features relevant to DR and ROP are extracted using dual channel based Capsule Network (CapsNet). After that, LeNet-5 receives the CapsNet feature map for categorization. To increase the deep learning classifier's performance, the Deep Convolutional Generative Adversarial Network (DCGAN) based data augmentation technique is implemented. The system evaluated in MESSIDOR and private datasets obtained 99.29% and 99.12% accuracy for DR and ROP classification. When the attained results are compared with other existing techniques, it is seen that more successful findings are achieved.

With the current push towards using fewer antipsychotics and more non-pharmacological interventions in long-term care, it has become increasingly important for knowledge and best-practice sharing across the province. The “Good Ideas” project began in 2001 in the context of my work as a Royal Ottawa geriatric psychiatry behavioural support outreach nurse to long-term-care facilities in Ottawa. A toolkit was begun as various ideas and tools were found to be useful in the management of behavioural challenges in the care of long term care residents. These non-pharmacological tools can have a significant impact on the management of behavioural challenges. Some were discovered via “out-of-the-box” thinking, some as a result of exploring possibilities on the Web, others were shared with me by colleagues in various roles and settings. I have worked in geriatric psychiatry in various capacities as a nurse at The Royal Ottawa Health Care Group since 1986, and have had the opportunity to accumulate several “good ideas” over time. I found myself carrying various articles, pamphlets, booklets, photos in my workbag and noticed I was being contacted more frequently over time on how to obtain certain items. When these non-pharmacological approaches were implemented, and successful, a common response would be: “what a good idea!” Thus, the name given to the project came to be. Good Ideas has grown over the years as the information has been shared with outreach team members and utilized in their own practice. All contacts are encouraged to share any new “good ideas” they encounter so those too can be added. Originally a hardcopy handout with a list and the resources to outsource items was created and distributed. This evolved into a PowerPoint presentation explaining the usefulness of each tool in specific target behaviours and how to obtain the tool, as well as photos. Later a poster was made and a second version was produced more recently. Currently the project is in the process of being translated to French for our bilingual Ottawa area. The project has circulated among my teammates to be used in education sessions in their long-term-care facilities or as an adjunct to larger full day education sessions on the topic of dementia care. A large colorful hatbox also contains some sample items to add to the hard copies. Good Ideas has been presented at the Regional Geriatric Program Annual Meeting poster presentation Oct 12, 2013, with very positive feedback from participants. Good Ideas is a project in perpetuity, with no stop date planned. It is my hope it will continue to grow long after my retirement date. It promotes the concept of creative thinking about behavioural challenges in dementia care, while supporting that pharmacological intervention should most often be as a last resort.

Background: Tuberculosis a major public health problem in India with highest burden of cases. India accounts for about 24% of global prevalence, 23% of the global incidence cases and 21% of global TB deaths. Irregular and inappropriate treatment of persons with active TB, unawareness about TB symptoms and treatment course, illiteracy, may be the major hurdles for TB eradication.Methods: A cross sectional, community based study was conducted in urban slum dwellers (n=153). Data compilation and analysis: All the data collected was entered and analyzed with MS excel software 2007 and Epi info 3.5.3. All tests were considered significant at p<0.05 level.Results: 18.3% told that cough+expectoration+evening rise of temperature+weight loss are the signs and symptoms of TB. 55.5% know that it spreads through cough and sneezing mixed with air. 23.5% knows blood examination, sputum examination, x-ray is the mode of diagnosis of TB.Conclusions: Literacy plays major role in creating awareness on TB.

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Background: Globally an estimated 422 million adults are living with Diabetes as per WHO data 2014, and 85 to 90% cases are type 2 diabetes. Maximum number of people with diabetes mellitus are in the age group of 40 to 59 yrs. Among them 50% are undiagnosed. Sedentary lifestyle, diet, dietary fiber, mal-nutrition, some chemical agents, stress, alcohol, viral infections, etc., are some environmental risk factors.Methods: A cross sectional, community based study. Details of the study subjects were recorded using structured predesigned and pretested questionnaire. All the data collected was entered and analyzed with MS Excel software 2007 and Epi info 3.5.3. All tests were considered significant at p <0.05 level.Results: In our study, majority of population participated in the screening camp are between 30 to 35 years of age, Female (53.2%) participants were more. We found that 38 (24.1%) persons were found to be in pre-diabetic stage, 57 (37.3%) are having high risk of getting diabetes.Conclusions: There is significant relationship between smoking, alcohol consumption and sedentary lifestyle (p<0.05) to the risk of diabetes as per Indian diabetes risk score.