Alzheimers Disease Diagnosis using Machine Learning: A Review

Alzheimers Disease AD is an acute neuro disease that degenerates the brain cells and thus leads to memory loss progressively. It is a fatal brain disease that mostly affects the elderly. It steers the decline of cognitive and biological functions of the brain and shrinks the brain successively, which in turn is known as Atrophy. For an accurate diagnosis of Alzheimers disease, cutting edge methods like machine learning are essential. Recently, machine learning has gained a lot of attention and popularity in the medical industry. As the illness progresses, those with Alzheimers have a far more difficult time doing even the most basic tasks, and in the worst case, their brain completely stops functioning. A persons likelihood of having early-stage Alzheimers disease may be determined using the ML method. In this analysis, papers on Alzheimers disease diagnosis based on deep learning techniques and reinforcement learning between 2008 and 2023 found in google scholar were studied. Sixty relevant papers obtained after the search was considered for this study. These papers were analysed based on the biomarkers of AD and the machine-learning techniques used. The analysis shows that deep learning methods have an immense ability to extract features and classify AD with good accuracy. The DRL methods have not been used much in the field of image processing. The comparison results of deep learning and reinforcement learning illustrate that the scope of Deep Reinforcement Learning DRL in dementia detection needs to be explored.Comment: 10 pages and 3 figure

Pseudocapacitors

World energy consumption has grown at a rate of knots. Economic growth, increasing prosperity and urbanization, the rise in per capita consumption, and the spread of energy access are the factors likely to considerably increase the total energy demand. In order to meet both the environmental and economic challenges, society realizes the necessity for harvesting the renewable resources, their storage, and recovery. To achieve accelerating clean energy innovation, cost reduction, and deployment of many clean energy technologies, it is important to formulating policies and their implementation, programmes for the development of new and renewable energy apart from coordinating and intensifying R&D in the sector. At present, aggravating energy and environmental issues, such as fossil fuel depletion, pollution problems, and global warming are ringing alarm bells to humans. Thus, there is an urgent need for enhanced energy security along with reducing greenhouse gas emissions. In this direction, renewable energy is one of the environmentally friendly sources of energy and effectiveness of growing economy of the whole world in general. The development of environmentally friendly materials is one of the key issues today

Proceedings of International Web Conference in Civil Engineering for a Sustainable Planet

This proceeding contains articles of the various research ideas of the academic community and practitioners accepted at the "International Web Conference in Civil Engineering for a Sustainable Planet (ICCESP 2021)". ICCESP 2021 is being Organized by the Habilete Learning Solutions, Kollam in Collaboration with American Society of Civil Engineers (ASCE), TKM College of Engineering, Kollam, and Baselios Mathews II College of Engineering, Kollam, Kerala, India. Conference Title: International Web Conference in Civil Engineering for a Sustainable PlanetConference Acronym: ICCESP 2021Conference Date: 05–06 March 2021Conference Location: Online (Virtual Mode)Conference Organizer: Habilete Learning Solutions, Kollam, Kerala, IndiaCollaborators: American Society of Civil Engineers (ASCE), TKM College of Engineering, Kollam, and Baselios Mathews II College of Engineering, Kollam, Kerala, India