Epidemiology of Eales Disease in the Central Western India

Objective: To investigate the clinical features and propose a new staging system based on the clinicopathological correlation and formulate new guidelines for management of Eales’ disease in healthy young males. Design: Prospective cohort study. Setting: Vitreo Retinal Department of a tertiary eye care center in Western Central India. Participants: Seventy-four eyes diagnosed with Eales’ disease. Materials and methods: From 2004 to 2010, patients clinically diagnosed with Eales’ disease were enrolled in this study using specific inclusion and exclusion criteria. We examined the patients’ anterior and posterior segments thoroughly. We performed the necessary ocular and systemic investigations. We divided the investigations into three stages: inflammatory, ischemic and complications and the patients were treated accordingly. We treated the patients using medical management, photocoagulation or pars plana vitrectomy. The patients were monitored according to standard schedules and formats. All information was documented using a pre-tested online format and statistical analyses were performed using SPSS ver. 17. A p-value < 0.05 was considered to indicate significance. Outcome measures: Visual acuity. Results: The cohort comprised 74 cases with a mean age of 30 ± 8.73 years. The visual acuity of the presenting cohort was < 3/60 in 64.9% of eyes. The final visual outcome was > 6/12 in 40 eyes (54.1%), 6/60 to 6/18 in 14 eyes (18.9%) and < 1/60 in the remaining 9 eyes at a mean follow-up of 592 days. The visual parameters differed significantly pre-and post-treatment. We evaluated the visual outcome following surgical management. Conclusion: We studied epidemiological facts about anterior and posterior segment findings

Epidemiology of Eales Disease in the Central Western India

Objective: To investigate the clinical features and propose a new staging system based on the clinicopathological correlation and formulate new guidelines for management of Eales’ disease in healthy young males. Design: Prospective cohort study. Setting: Vitreo Retinal Department of a tertiary eye care center in Western Central India. Participants: Seventy-four eyes diagnosed with Eales’ disease. Materials and methods: From 2004 to 2010, patients clinically diagnosed with Eales’ disease were enrolled in this study using specific inclusion and exclusion criteria. We examined the patients’ anterior and posterior segments thoroughly. We performed the necessary ocular and systemic investigations. We divided the investigations into three stages: inflammatory, ischemic and complications and the patients were treated accordingly. We treated the patients using medical management, photocoagulation or pars plana vitrectomy. The patients were monitored according to standard schedules and formats. All information was documented using a pre-tested online format and statistical analyses were performed using SPSS ver. 17. A p-value < 0.05 was considered to indicate significance. Outcome measures: Visual acuity. Results: The cohort comprised 74 cases with a mean age of 30 ± 8.73 years. The visual acuity of the presenting cohort was < 3/60 in 64.9% of eyes. The final visual outcome was > 6/12 in 40 eyes (54.1%), 6/60 to 6/18 in 14 eyes (18.9%) and < 1/60 in the remaining 9 eyes at a mean follow-up of 592 days. The visual parameters differed significantly pre-and post-treatment. We evaluated the visual outcome following surgical management. Conclusion: We studied epidemiological facts about anterior and posterior segment findings

Credibility Analysis of User-Designed Content Using Machine Learning Techniques

Content is a user-designed form of information, for example, observation, perception, or review. This type of information is more relevant to users, as they can relate it to their experience. The research problem is to identify the credibility and the percentage of credibility as well. Assessment of such content is important to convey the right understanding of the information. Different techniques are used for content analysis, such as voting the content, Machine Learning Techniques, and manual assessment to evaluate the content and the quality of information. In this research article, content analysis is performed by collecting the Movie Review dataset from Kaggle. Features are extracted and the most relevant features are shortlisted for experimentation. The effect of these features is analyzed by using base regression algorithms, such as Linear Regression, Lasso Regression, Ridge Regression, and Decision Tree. The contribution of the research is designing a heterogeneous ensemble regression algorithm for content credibility score assessment, which combines the above baseline methods. Moreover, these factors are also toned down to obtain the values closer to Gradient Descent minimum. Different forms of Error Loss, such as Mean Absolute Error, Mean Squared Error, LogCosh, Huber, and Jacobian, and the performance is optimized by introducing the balancing bias. The accuracy of the algorithm is compared with induvial regression algorithms and ensemble regression separately; this accuracy is 96.29%

A Study of the Recent Trends of Immunology : Key Challenges, Domains, Applications, Datasets, and Future Directions

The human immune system is very complex. Understanding it traditionally required specialized knowledge and expertise along with years of study. However, in recent times, the introduction of technologies such as AIoMT (Artificial Intelligence of Medical Things), genetic intelligence algorithms, smart immunological methodologies, etc., has made this process easier. These technologies can observe relations and patterns that humans do and recognize patterns that are unobservable by humans. Furthermore, these technologies have also enabled us to understand better the different types of cells in the immune system, their structures, their importance, and their impact on our immunity, particularly in the case of debilitating diseases such as cancer. The undertaken study explores the AI methodologies currently in the field of immunology. The initial part of this study explains the integration of AI in healthcare and how it has changed the face of the medical industry. It also details the current applications of AI in the different healthcare domains and the key challenges faced when trying to integrate AI with healthcare, along with the recent developments and contributions in this field by other researchers. The core part of this study is focused on exploring the most common classifications of health diseases, immunology, and its key subdomains. The later part of the study presents a statistical analysis of the contributions in AI in the different domains of immunology and an in‐depth review of the machine learning and deep learning methodologies and algorithms that can and have been applied in the field of immunology. We have also analyzed a list of machine learning and deep learning datasets about the different subdomains of immunology. Finally, in the end, the presented study discusses the future research directions in the field of AI in immunology and provides some possible solutions for the same.

Management of Diabetes in Long-term Care and Skilled Nursing Facilities: A Position Statement of the American Diabetes Association

Diabetes is more common in older adults, has a high prevalence in long-term care (LTC) facilities, and is associated with significant disease burden and higher cost. The heterogeneity of this population with regard to comorbidities and overall health status is critical to establishing personalized goals and treatments for diabetes. The risk of hypoglycemia is the most important factor in determining glycemic goals due to the catastrophic consequences in this population. Simplified treatment regimens are preferred, and the sole use of sliding scale insulin (SSI) should be avoided. This position statement provides a classification system for older adults in LTC settings, describes how diabetes goals and management should be tailored based on comorbidities, delineates key issues to consider when using glucose-lowering agents in this population, and provides recommendations on how to replace SSI in LTC facilities. As these patients transition from one setting to another, or from one provider to another, their risk for adverse events increases. Strategies are presented to reduce these risks and ensure safe transitions. This article addresses diabetes management at end of life and in those receiving palliative and hospice care. The integration of diabetes management into LTC facilities is important and requires an interprofessional team approach. To facilitate this approach, acceptance by administrative personnel is needed, as are protocols and possibly system changes. It is important for clinicians to understand the characteristics, challenges, and barriers related to the older population living in LTC facilities as well as the proper functioning of the facilities themselves. Once these challenges are identified, individualized approaches can be designed to improve diabetes management while lowering the risk of hypoglycemia and ultimately improving quality of life