RESUMO
Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology, significantly impacting the diagnosis and treatment of neurological disorders. Recent technological breakthroughs have given us access to a plethora of information relevant to many aspects of neurology. Neuroscience and AI share a long history of collaboration. Along with great potential, we encounter obstacles relating to data quality, ethics, and inherent difficulty in applying data science in healthcare. Neurological disorders pose intricate challenges due to their complex manifestations and variability. Automating image interpretation tasks, AI algorithms accurately identify brain structures and detect abnormalities. This accelerates diagnosis and reduces the workload on medical professionals. Treatment optimization benefits from AI simulations that model different scenarios and predict outcomes. These AI systems can currently perform many of the sophisticated perceptual and cognitive capacities of biological systems, such as object identification and decision making. Furthermore, AI is rapidly being used as a tool in neuroscience research, altering our understanding of brain functioning. It has the ability to revolutionize healthcare as we know it into a system in which humans and robots collaborate to deliver better care for our patients. Image analysis activities such as recognizing particular brain regions, calculating changes in brain volume over time, and detecting abnormalities in brain scans can be automated by AI systems. This lessens the strain on radiologists and neurologists while improving diagnostic accuracy and efficiency. It is now obvious that cutting-edge artificial intelligence models combined with high-quality clinical data will lead to enhanced prognostic and diagnostic models in neurological illness, permitting expert-level clinical decision aids across healthcare settings. In conclusion, AI's integration into neurology has revolutionized diagnosis, treatment, and research. As AI technologies advance, they promise to unravel the complexities of neurological disorders further, leading to improved patient care and quality of life. The symbiosis of AI and neurology offers a glimpse into a future where innovation and compassion converge to reshape neurological healthcare. This abstract provides a concise overview of the role of AI in neurology and its transformative potential.
RESUMO
Diabetes mellitus is a chronic metabolic disorder with increasing prevalence per hour. Cataracts are one of the most common eye complications, and they affect all structures of the eye. The incidence of cataracts is increasing in patients with diabetes by several mechanisms. With the advancement of technology, cataract surgery is now a necessary procedure for diabetic patients. High-risk complications, like diabetic macular oedema, diabetic retinopathy (DR), phakic, postoperative cyst, and postoperative macular oedema, and macular oedema and endophthalmitis following surgery for a pseudocyst, could result in blindness. The importance of preoperative, intraoperative, and postoperative factors cannot be overestimated in managing complications and improving visual outcomes. DR can be a severe problem if it worsens and causes non-proliferative or proliferative DR or if fluid accumulation in the eye is diagnosed as macular oedema. A woman progressing to sight-threatening DR during childbearing age experiences distress and often requires ocular treatment. Diabetes that has been present for a more extended period, as well as more significant hyperglycaemia, hypertension, cardiovascular diseases, and elevated blood pressure, substantially predict the development of DR. Oxidative stress can be caused by hyperglycaemia, irregular metabolic processes, and people with DR developing neurodegeneration. Therefore, controlling postprandial hyperglycaemia is crucial for preventing DR. Femtosecond laser technology, multifocal intraocular lenses, and other surgical innovations are popularly referred to as surgical management; it will be engaged in the coming era to determine whether there will be a continued reduction in the complication of cataract surgery. This article aims to review the correlation of DR with stroke and its screening and to outline the critical management strategies.
