Alzheimer's disease (AD) is the leading cause of dementia, affecting approximately 60-80% of dementia cases. It is a progressive neurodegenerative disorder primarily impacting older adults, characterized by cognitive decline, memory loss, impaired thinking, and behavioral changes. The disease poses a significant global health challenge due to its increasing prevalence, driven by aging populations and longer life expectancies. AD is characterized by the accumulation of Amyloid beta (Aβ) plaques and neurofibrillary tangles, which disrupt neuronal function and contribute to neurodegeneration. Genetic, environmental, and lifestyle factors play crucial roles in the disease's pathogenesis. Diagnosis of AD involves cognitive and behavioral tests, blood and cerebrospinal fluid (CSF) tests, neurological examinations, and brain imaging. CSF levels of Aβ40/42 and p-tau181/Aβ42 are key biomarkers, but CSF analysis is invasive. Non-invasive biomarkers and radiolabeled tracers are being developed for early diagnosis. Neuroimaging techniques, including MRI, CT, PET, and fMRI, aid in confirming the diagnosis, assessing disease severity, and differentiating AD from other forms of dementia. Therapeutic strategies for AD include FDA-approved pharmacological interventions such as cholinesterase inhibitors and NMDA receptor antagonists, as well as novel drug targets and disease-modifying therapies. Cholinesterase inhibitors increase acetylcholine levels, improving cognitive function. NMDA receptor antagonists protect neurons from excitotoxicity. Anti-amyloid therapies aim to reduce Aβ accumulation, while anti-tau therapies target tau pathology. AI techniques, such as machine learning and deep learning, are being integrated into AD diagnosis and treatment to improve accuracy and efficiency. Overall, the integration of biomarkers, cognitive testing, and AI techniques offers valuable tools for improving early detection, providing accurate diagnoses, and monitoring disease progression, ultimately facilitating timely interventions and personalized care for individuals with AD.Alzheimer's disease (AD) is the leading cause of dementia, affecting approximately 60-80% of dementia cases. It is a progressive neurodegenerative disorder primarily impacting older adults, characterized by cognitive decline, memory loss, impaired thinking, and behavioral changes. The disease poses a significant global health challenge due to its increasing prevalence, driven by aging populations and longer life expectancies. AD is characterized by the accumulation of Amyloid beta (Aβ) plaques and neurofibrillary tangles, which disrupt neuronal function and contribute to neurodegeneration. Genetic, environmental, and lifestyle factors play crucial roles in the disease's pathogenesis. Diagnosis of AD involves cognitive and behavioral tests, blood and cerebrospinal fluid (CSF) tests, neurological examinations, and brain imaging. CSF levels of Aβ40/42 and p-tau181/Aβ42 are key biomarkers, but CSF analysis is invasive. Non-invasive biomarkers and radiolabeled tracers are being developed for early diagnosis. Neuroimaging techniques, including MRI, CT, PET, and fMRI, aid in confirming the diagnosis, assessing disease severity, and differentiating AD from other forms of dementia. Therapeutic strategies for AD include FDA-approved pharmacological interventions such as cholinesterase inhibitors and NMDA receptor antagonists, as well as novel drug targets and disease-modifying therapies. Cholinesterase inhibitors increase acetylcholine levels, improving cognitive function. NMDA receptor antagonists protect neurons from excitotoxicity. Anti-amyloid therapies aim to reduce Aβ accumulation, while anti-tau therapies target tau pathology. AI techniques, such as machine learning and deep learning, are being integrated into AD diagnosis and treatment to improve accuracy and efficiency. Overall, the integration of biomarkers, cognitive testing, and AI techniques offers valuable tools for improving early detection, providing accurate diagnoses, and monitoring disease progression, ultimately facilitating timely interventions and personalized care for individuals with AD.