Artificial Intelligence and Digital Biomarkers: An Advanced Perspective in Diagnosing Alzheimer's Disease

Abstract

Alzheimer's disease is a neurological disorder that progressively degrades the brain cells, leading to a gradual decline in cognitive and behavioural functions. In the year 2022, Alzheimer's disease was the seventh largest cause of death in the United States, as reported by the Centers for Disease Control and Prevention (CDC). AI-based tools help the psychiatrists and other health care professionals in diagnosing the Alzheimer's disease. AI keeps track of the patient prognosis and their response to the treatment. AI could change the way of health care professionals learn by showing them the diagnostic patterns and insights that other methods don't. Patients will become more likely to adhere to their treatment plans because AI comforts the patients to get involved by using the data driven visuals and personalized explanations. This review focuses on the role of artificial intelligence in diagnosing Alzheimer's Disease and the initiatives & technological innovations along with the new advancements in AI-augmented analysis of individual digital biomarkers. This review also highlights the importance of AI Predictive Models for Alzheimer's disease and the concept of Federated Learning and Privacy-Preserving AI. The existing approaches of detecting Alzheimer's disease might be transformed if AI models are developed with proper ethics, clinical validation and high-quality data as priorities. The enhanced efficiency of healthcare delivery is a direct consequence of these instruments' capacity to assist the health care professionals in performing the early diagnoses and delivering superior treatment and enhanced patient care.

Ähnliche Arbeiten