# Alzheimer's Disease Diagnosis Using Machine Learning: A Survey
## 2 Alzheimer's Disease
Frequently employed techniques, such as repetition and written and verbal rehearsal of words or letters, are commonly utilized to enhance memory in individuals who are in good health. In recent times, there has been a growing focus on the potential of neurofeedback systems to improve cognitive processes, particularly memory, owing to their distinctive capabilities. Neurofeedback involves the acquisition of electroencephalographic (EEG) signals via electrodes placed on the scalp, which are subsequently presented to an individual through a computer interface for feedback purposes. By manipulating an individual's mental state, alterations in the amplitude of the EEG signal across various frequencies can be observed and displayed on a monitor [69]. Consequently, the individual endeavors to modify the patterns of their brain signals to attain predetermined objectives. In the context of neurofeedback, individuals acquire the ability to regulate their brain signals by modulating the corresponding mental states [70; 71; 72]. Alzheimer's disease is a neurological disorder resulting in the degeneration of brain tissues, leading to the death of nerve cells in specific brain regions. Cell death results in losing fundamental cognitive abilities, including recalling individuals' names or recognizing their faces. Alzheimer's disease is characterized by a gradual decline in cognitive skills, resulting in a pervasive and irreversible impact on various aspects of an individual's memory, as reported in the literature [73]. Alzheimer's disease ranks as the sixth most prevalent cause of mortality globally. The progression of medical science has led to the proposition that a hereditary inclination may contribute to transmitting a disease among forthcoming generations within a familial lineage. The domestic genetic factor is widely recognized as a significant contributor to the onset of Alzheimer's disease. Individuals within a family diagnosed with Alzheimer'sexhibit a higher likelihood of familial susceptibility within the same generation or across multiple generations. The process of brain development is influenced, to some extent, by an individual's genetic makeup. Furthermore, a correlation has been established between the onset of Alzheimer's disease and a reduction in brain volume over a while. The genetic factor appears to hold potential as a primary indicator in the diagnostic process of Alzheimer's disease. The phenomenon above is not an anomaly in the context of Alzheimer's disease. However, it is contingent upon genetic predispositions rather than environmental influences [74; 75; 76; 77; 78]. Alterations in cognitive function and brain structure are frequently a result of aging, a natural phenomenon. However, the clinical manifestations of Alzheimer's disease extend beyond transient and uncomplicated memory loss. Individuals diagnosed with Alzheimer's encounter communication, learning, cognition, and logical reasoning difficulties, which can significantly impact familial dynamics, occupational settings, and other related areas. Alzheimer's disease is characterized by a range of symptoms, such as memory impairment, difficulty executing routine tasks, reduced expressive abilities, impaired spatial and temporal orientation, compromised judgment, cognitive deficits, apraxia, altered mood and behavior, personality changes, loss of motivation, and other related manifestations [79]. The onset of symptoms associated with Alzheimer's is typically delayed, rendering its diagnosis challenging and often only possible during the later stages of the disease. Consequently, developing intelligent medical systems for the timely detection of the ailment above is deemed imperative. Given that medical image analysis is a prevalent diagnostic technique, numerous research endeavors have been undertaken in this domain. The non-invasive nature of image processing and analysis methods in medical imaging is a crucial factor that has been selected as a significant aspect of this investigation [68; 79].