Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease

Year : 2026 | Volume : 03 | Issue : 02 | Page : 15 27
    By

    Rohit Saroha,

  • Chetna Chhabra,

  • Abhishek Kumar,

  • Gauri Mudgal,

  1. Assistant Professor, Department of Physiology, Venkateshwara Institute of Medical Sciences, Gajraula, Amroha, Uttar Pradesh, India
  2. MD Resident, Department of Medicine, Santosh Deemed to be University, Ghaziabad, Uttar Pradesh, India
  3. Assistant Professor, Department of Pharmacy, Acharya Dhrubhasa College of Health Care Education, Sitamarhi, Bihar,, Sitamarhi, Bihar,, India
  4. PhD Scholar and Assistant Professor, Department of Physiology, Divya Jyoti College of Dental Sciences and Research, Modinagar, Uttar Pradesh,, India

Abstract

Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent developments in AI, specifically machine learning, deep learning, natural language processing, and predictive analytics, have greatly enhanced the capacity to detect subtle patterns of diseases influenced by complex multimodal data. The AI analysis of magnetic resonance imaging (MRI), positron emission tomography (PET), cerebrospinal fluid biomarkers, blood biomarkers, genomic data, speech patterns, and digital health data has shown incredible prospects of improving the diagnostic accuracy and allowing early detection of the Alzheimer disease. In addition, AI can facilitate precision medicine by combining both patient-specific clinical, genetic, environmental, and lifestyle data to create personalized treatment approaches and maximize therapeutic decision-making. Innovative uses of AI, including treatment planning, disease progression forecasting, digital therapeutics, wearables, and remote monitoring are all part of increasingly proactive and patient-centered healthcare provision. Explainable AI is also enhancing the transparency and clinical acceptance of AI-based decision-support systems. Notwithstanding its promising prospects, issues concerning data privacy, algorithm bias, interpretability, regulatory approval, and clinical validation should be considered as crucial factors to the wider implementation. This review provides an overview of the existing uses of artificial intelligence in early diagnosis and personalized treatment of Alzheimer disease, emphasizing recent technological developments, clinical uses, current limitations and opportunities. Further adoption of AI in neurology can transform the care of dementia using predictive, preventive, and tailored healthcare practices that enhance patient outcomes and quality of life

Keywords: Alzheimer’s Disease, Artificial Intelligence, Machine Learning, Early Diagnosis, Precision Medicine

[This article belongs to International Journal of Brain Sciences ]

How to cite this article:
Rohit Saroha, Chetna Chhabra, Abhishek Kumar, Gauri Mudgal. Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease. International Journal of Brain Sciences. 2026; 03(02):15-27.
How to cite this URL:
Rohit Saroha, Chetna Chhabra, Abhishek Kumar, Gauri Mudgal. Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease. International Journal of Brain Sciences. 2026; 03(02):15-27. Available from: https://journals.stmjournals.com/ijbs/article=2026/view=247576


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Regular Issue Subscription Review Article
Volume 03
Issue 02
Received 04/06/2026
Accepted 13/06/2026
Published 25/06/2026
Publication Time 21 Days
32

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