Retinal Imaging in Alzheimer’s Disease

Identifying biomarkers of Alzheimer's disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies. Developments in non-invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study neuronal and vascular structures in the retina in people with AD. Both qualitative and quantitative measurements from these retinal imaging technologies (eg, thinning of peripapillary retinal nerve fibre layer, inner retinal layer, and choroidal layer, reduced capillary density, abnormal vasodilatory response) have been shown to be associated with cognitive function impairment and risk of AD. The development of computer algorithms for respective retinal imaging methods has further enhanced the potential of retinal imaging as a viable tool for rapid, early detection and screening of AD. In this review, we present an update of current retinal imaging techniques and their potential applications in AD research. We also discuss the newer retinal imaging techniques and future directions in this expanding field

Is the Eye an Extension of the Brain in Central Nervous System Disease?

Since 1950, global average life expectancy has been steadily increasing at a rate of more than 3 years per decade (with the exception of the 1990s), with accompanying growth in age-related neurodegenerative diseases, such as Alzheimer's (AD), Parkinson's (PD), amyotrophic lateral sclerosis (ALS), multiple sclerosis (MS), and stroke. The limited capacity of self-repair of the adult mammalian central nervous system (CNS) and the general lack of preventive and restorative treatments for these conditions lead to progressive debilitation and eventually death. Not only does this result in a diminished quality of life for patients (and their families) but also impacts society by placing tremendous demands on social welfare and health systems. How to “ensure healthy lives and promote well-being for all at all ages,” one of the Sustainable Development Goals for 2030, adopted by the United Nations General Assembly, is thus a challenge to be tackled by the next generation of researchers, clinicians, and policy makers

Applications of Artificial Intelligence in Healthcare

Now in these days, artificial intelligence (AI) is playing a major role in healthcare. It has many applications in diagnosis, robotic surgeries, and research, powered by the growing availability of healthcare facts and brisk improvement of analytical techniques. AI is launched in such a way that it has similar knowledge as a human but is more efficient. A robot has the same expertise as a surgeon; even if it takes a longer time for surgery, its sutures, precision, and uniformity are far better than the surgeon, leading to fewer chances of failure. To make all these things possible, AI needs some sets of algorithms. In Artificial Intelligence, there are two key categories: machine learning (ML) and natural language processing (NPL), both of which are necessary to achieve practically any aim in healthcare. The goal of this study is to keep track of current advancements in science, understand technological availability, recognize the enormous power of AI in healthcare, and encourage scientists to use AI in their related fields of research. Discoveries and advancements will continue to push the AI frontier and expand the scope of its applications, with rapid developments expected in the future

Artificial intelligence extension of the OSCAR-IB criteria

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines

Is attention all you need in medical image analysis? A review

Medical imaging is a key component in clinical diagnosis, treatment planning and clinical trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance gains in medical image analysis (MIA) over the last years. CNNs can efficiently model local pixel interactions and be trained on small-scale MI data. The main disadvantage of typical CNN models is that they ignore global pixel relationships within images, which limits their generalisation ability to understand out-of-distribution data with different 'global' information. The recent progress of Artificial Intelligence gave rise to Transformers, which can learn global relationships from data. However, full Transformer models need to be trained on large-scale data and involve tremendous computational complexity. Attention and Transformer compartments (Transf/Attention) which can well maintain properties for modelling global relationships, have been proposed as lighter alternatives of full Transformers. Recently, there is an increasing trend to co-pollinate complementary local-global properties from CNN and Transf/Attention architectures, which led to a new era of hybrid models. The past years have witnessed substantial growth in hybrid CNN-Transf/Attention models across diverse MIA problems. In this systematic review, we survey existing hybrid CNN-Transf/Attention models, review and unravel key architectural designs, analyse breakthroughs, and evaluate current and future opportunities as well as challenges. We also introduced a comprehensive analysis framework on generalisation opportunities of scientific and clinical impact, based on which new data-driven domain generalisation and adaptation methods can be stimulated

Ocular manifestations of Parkinson disease

Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder. We aimed to review both the disease and the drug-related ocular manifestations of PD. Methods: In this manuscript, we have reviewed and summarized existing literature on the ocular manifestations and drug-related complications of PD. We have also discussed the use of current noninvasive imaging techniques, such as optical coherence tomography (OCT), for the early diagnosis and monitoring of PD. Results: Impaired color vision, reduced stereopsis, reduced contrast sensitivity, pupillary abnormalities, eye movement disorders, convergence insufficiency, dry eye syndrome, glaucoma, visual dysfunctions, retinal abnormalities, and drug-related side effects were among the listed ocular manifestations of PD. There is a large knowledge gap regarding the type of glaucoma affecting PD patients—whether it is open-angle or other types. Further case studies and long-term follow-ups during PD progression are necessary to fill this gap. Patient compliance with follow-up visits for more visual field tests and OCT during PD progression may become problematic when dementia and cognitive impairment occur. Conclusions: There is a general need for clinicians to perform further tests and more visual examinations to rule out ocular manifestations. Furthermore, additional clinical trials are needed to further evaluate the use of different types of OCT findings as biomarkers of PD progression. This would aid in early diagnosis and in delaying disease progression, if treated promptly

Immunological and inflammatory aspects of age-related macular degeneration measured by quantitative immunohistochemical techniques

Relatório de estágio do mestrado em Gestão, apresentado à Faculdade de Economia da Universidade de Coimbra, sob a orientação de António Martins e Luís Albano.No âmbito do Mestrado em Gestão da Faculdade de Economia da Universidade de Coimbra, foi realizado um estágio curricular na Nextconsulting SA, que decorreu de 2 de fevereiro de 2015 a 6 de Junho de 2015. Como resultado desse estágio é apresentado este trabalho, no qual o tema foi sugerido pela empresa que demonstrou interesse numa análise comparativa entre o imposto sobre o rendimento das sociedades em Portugal e em Angola, uma vez que consideram uma informação útil, dado que operam também em Angola. Sendo que o imposto sobre o rendimento das sociedades tem inúmeras características, seria demasiado extenso e complexo abordá-las todas neste trabalho. Assim sendo, optámos pelos seguintes pontos: gastos e perdas aceites fiscalmente, depreciações, provisões e taxas, que, a nosso ver, são da maior relevância. Este relatório começa com uma revisão da literatura e legislação sobre o tema no geral e, seguidamente, aprofunda cada um dos pontos. Prossegue com a apresentação da empresa de acolhimento assim como das tarefas desenvolvidas ao longo do período de estágio. Finalizando com um caso ilustrativo que demonstra qual seria o imposto a pagar de uma empresa fictícia se tivesse sede em Portugal em comparação com o imposto a pagar se a mesma empresa tivesse sede em Angola. Um ponto relevante neste relatório é o facto do sistema fiscal angolano ter tido a sua origem no sistema que vigorou em Portugal no período anterior às últimas reformas, tendo-lhes servido de exemplo e o que leva a que existam fortes semelhanças entre estes dois países. Em Portugal, este imposto caracteriza-se por ter uma taxa nominal relativamente elevada, o que não é benéfico em termos de concorrência fiscal elevada. Porém, Angola apresenta uma taxa nominal igualmente elevada, sendo necessário o alargamento da base tributária e a celebração de Convenções de Dupla Tributação, de modo a poder atrair investidores estrangeiros. Através do exemplo prático, verificámos que empresas nas mesmas condições pagariam menos imposto em Portugal do que em Angola, sendo que a principal razão responsável por esta situação é a diferença na taxa de tributação