Artificial intelligence opens diagnostic door for predicting brain diseases

Alzheimer’s disease is a chronic neurodegenerative condition with a tremendous socio-economic impact worldwide. The past decade has witnessed significant strides in comprehending some of the underlying mechanisms responsible for it, and in developing new diagnostic tools for the disease. For instance, new brain imaging techniques, including MRI (magnetic resonance imaging), have revolutionized the field by providing valuable insights into the early changes in the brains of individuals with Alzheimer’s disease. These imaging modalities enable the detection of early markers such as amyloid-6 plaques and tau protein deposits in the brain, facilitating an early and precise diagnosis. Furthermore, the emerging technologies encompassing the measure of compounds in the blood (a.k.a. blood-based markers) exhibit promising results in the identification of specific subtypes of Alzheimer’s disease at its earliest stages.

Interestingly, today advancements in diverse computer technologies, including artificial intelligence and deep learning, are offering new hope for the development of better diagnostic approaches in medical areas including 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 tools particularly when there is a need to analyze very complex numbers and datasets that typically characterize them. To this end, we are witnessing a revolution since currently some of the most used diagnostic brain imaging approaches in Alzheimer’s disease research are being combined with these new tools of artificial intelligence allowing to significantly shorten the time needed for a diagnosis.

There is no doubt that these advancements hold immense potential not only for early detection but also for possible intervention strategies, thereby paving the way for new therapeutic opportunities and ultimately augmenting the quality of life for individuals affected by the disease. Overall, the recent technical advancements have opened new possibilities for analyzing complex brain imaging data and extracting valuable insights that would normally take a long time like days or weeks in a much shorter time like hours.

By utilizing artificial intelligence, we have been able to explore and identify substances in the blood (aka, markers) that unravel the underlying brain damage and progression of Alzheimer’s disease. This integration enables the accurate detection and classification of the
disease, providing early diagnostic clues and information on how the disease progresses.

In summary, the synergistic combination of artificial intelligence with brain imaging approaches holds immense promise in transforming our understanding of Alzheimer’s disease and has the potential to advance the development of novel diagnostic tools and hopefully therapy. Although challenges persist in finding a cure for Alzheimer’s disease, the advent of artificial intelligence offers optimism for enhanced disease management and a better comprehensive support for individuals affected by this devastating disease. 

Dr. Domenico Praticò is the director of the Alzheimer’s Center at the Lewis Katz School of Medicine at Temple University, Philadelphia.