What artificial intelligence can do for Alzheimer’s disease? ~ Domenico Pratico, MD, FCPP
- May 13, 2024

Alzheimer’s disease is a chronic neurodegenerative disorder with a tremendous socio-economic
impact worldwide. The past decade has witnessed significant strides in comprehending the
underlying pathophysiological mechanisms and developing diagnostics for the disease. For instance,
current neuroimaging techniques, including positron emission tomography and magnetic resonance
imaging, have revolutionized the field by providing valuable insights into the structural and
functional alterations in the brains of individuals with Alzheimer’s disease. These imaging modalities
enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles in the
brain, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing
blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of
specific molecular signatures for Alzheimer’s disease at its earliest stages.
Interestingly, today advancements in diverse computational technologies, including artificial
intelligence and deep learning, are offering new hope for the development of superior diagnostic
approaches in medical areas related to imaging, including in the field of neurodegenerative diseases
like Alzheimer’s disease. Regarding Alzheimer’s disease, the integration of machine learning
algorithms and artificial intelligence tools has enhanced the predictive capacity of most of these
imaging diagnostic means particularly when analyzing complex datasets that typically characterize
them. To this end, we are witnessing a silent revolution since currently some of the most used
diagnostic imaging approaches in neurodegeneration research are being combined with these new
tools of machine learning and artificial intelligence. This fact emphasizes the new notion about their
useful application in the realm of Alzheimer’s disease diagnostic.
There is no doubt that these advancements hold immense potential not only for early detection but
also for intervention strategies, thereby paving the way for personalized therapeutic opportunities
and ultimately augmenting the quality of life for individuals affected by Alzheimer’s disease. Overall,
these recent technical approaches have opened new possibilities for analyzing complex
neuroimaging data and extracting valuable insights that would normally take a long time in a much
shorter time. By utilizing artificial intelligence algorithms, researchers have been able to explore and
identify neuroimaging biomarkers that unravel the underlying pathology and progression of
Alzheimer’s disease. This integration enables the accurate detection and classification of the disease,
providing early diagnostic information and aiding in the understanding of disease mechanisms.
Additionally, artificial intelligence-driven neuroimaging techniques have the potential to improve
prediction models for disease progression and facilitate personalized treatment strategies.
In summary, the synergistic combination of artificial intelligence with neuroimaging approaches
holds immense promise in transforming our understanding of Alzheimer’s disease and has the
potential to advance the development of improved diagnostic tools and therapy. Although
challenges persist in finding a cure for Alzheimer’s disease, the advent of artificial intelligence
methodologies and techniques in aid of neuroimaging diagnostic advancements offer optimism for
enhanced disease management and a better comprehensive support for individuals affected by the
disease.
Domenico Praticò, MD, is the Scott Richards North Star Charitable Foundation Chair for Alzheimer’s Research, Professor and Director of the Alzheimer’s Center at Temple, and Professor of Pharmacology at the Lewis Katz School of Medicine at Temple University
You can find out more information on Dr. Domenico Pratico’s research papers here.
Follow Dr Domenico Pratico‘s lab website here: Pratico Lab