Alzheimer's disease (AD) is a brain illness that causes gradual memory loss. AD has no treatment and cannot be cured, so early detection is critical. Various AD diagnosis approaches are used in this regard, but Magnetic Resonance Imaging (MRI) provides the most helpful neuroimaging tool for detecting AD. In this paper, we employ a DenseNet-201 based transfer learning technique for diagnosing different Alzheimer's stages as Non-Demented (ND), Moderate Demented (MOD), Mild Demented (MD), Very Mild Demented (VMD), and Severe Demented (SD). The suggested method for a dataset of MRI scans for Alzheimer's disease is divided into five classes. Data augmentation methods were used to expand the size of the dataset and increase DenseNet-201's accuracy. It was found that the proposed strategy provides a very high classification accuracy. This practical and reliable model delivers a success rate of 98.24%. The findings of the experiments demonstrate that the suggested deep learning approach is more accurate and performs well compared to existing techniques and state-of-the-art methods.
This review (with 99 refs.) summarizes the progress that has been made in colorimetric (i.e. spectrophotometric) determination of organophosphate pesticides (OPPs) using gold and silver nanoparticles (NPs). Following an introduction into the field, a first large section covers the types and functions of organophosphate pesticides. Methods for colorimetric (spectrophotometric) measurements including RGB techniques are discussed next. A further section covers the characteristic features of gold and silver-based NPs. Syntheses and modifications of metal NPs are covered in section 5. This is followed by overviews on enzyme inhibition-based assays, aptamer-based assays and chemical (non-enzymatic) assays, and a discussion of specific features of colorimetric assays. Several Tables are presented that give an overview on the wealth of methods and materials. A concluding section addresses current challenges and discusses potential future trends and opportunities. Graphical abstractSchematic representation of organophosphate pesticide determinations based on aggregation of nanoparticles (particular silver or gold nanoparticles). This leads to a color change which can be determined visually and monitored by a red shift in the absorption spectrum.