Artificial Intelligence Innovation in Alzheimer's Disease Care, Diagnosis, Treatment, and Integration

Alzheimer's disease (AD) is a progressive illness that impacts daily activity, thinking, and memory. Conventional diagnosis and therapy are burdensome given delayed drug development, delayed detection, and inadequate support for caregivers and patients. To fill these gaps AI has become a useful resource providing new data-driven approaches to controlling AD. AI innovation in patient care, diagnosis, treatment, and integration in healthcare is explored in this article. Machine learning that previously employed imaging methods such as MRI, PET, and CT enhances mild cognitive impairment diagnosis and follows the disease progression when coupled with tools such as the Alzheimer's disease Neuroimaging Initiative (ADNI). Natural language processing facilitates early screening and improves cognitive and linguistic testing. Through the analysis of current drugs, creation of new therapeutic drugs, forecasting patient reactions to medication, and performing virtual molecular docking, which accelerates discovery, AI assists with the therapeutic process. In patient care, AI-enabled digital therapies, smart assistive technology, chatbots, and remote monitoring features provide caregivers improved support, daily care, and cognitive rehabilitation. With AI integrated into the health care system by telemedicine, electronic health records, and real-time decision support, clinical decision making can be enhanced. But data quality, clarity of models, law, cost, and access problems still have to be addressed. In the future, ensuring responsible usage will necessitate interdisciplinary collaboration and ethics. With its potential to enhance clinical outcomes and quality of life, AI presents an attractive strategy to enhance Alzheimer's disease diagnosis, treatment, and care in general.

Keywords: Artificial intelligence (AI), MRI, Positron emission tomography (PET), Alzheimer's Disease Neuroimaging Initiative (ADNI), Electronic Health Records, Machine learning (ML), Deep Learning (DL).