A number of life threatening neuro-degenerative disorders had degraded the quality of life for the older generation in particular. Dementia is one such symptom which may lead to a severe condition called Alzheimer's disease if not detected at an early stage. It has been reported that the progression of such disease from a normal stage is due to the change in several parameters inside the human brain. In this paper, an innovative metaheuristic algorithms based ViT model has been proposed for the identification of dementia at different stage. A sizeable number of test data have been utilized for the validation of the proposed scheme. It has also been demonstrated that our model exhibits superior performance in terms of accuracy, precision, recall as well as F1-score.

翻译：多种危及生命的神经退行性疾病严重降低了老年人群的生活质量。痴呆症是其中之一，若未能在早期阶段检测，可能发展为称为阿尔茨海默病的严重病症。已有研究表明，此类疾病从正常阶段发展的原因是人脑内部多个参数的变化。本文提出了一种基于创新性元启发式算法的ViT模型，用于不同阶段痴呆症的识别。为验证所提方案，我们采用了大量测试数据。实验结果证明，该模型在准确率、精确率、召回率以及F1-score等指标上均展现出优越性能。