By Rasheed Sobowale

Artificial intelligence is playing an increasingly vital role in healthcare, and Nigerian researcher Elijah Alabi is among those leading efforts to apply it to the study of Alzheimer’s disease. He was recently honored in the United States with a research award recognizing his contributions to developing AI methods that can improve early diagnosis and personalized treatment for Alzheimer’s disease and related dementias, which affect millions of older adults worldwide

Alabi, who is currently pursuing a doctoral degree at the University of Denver in the United States, was selected for the 2025 Doctoral Scholar Award by KIHA, a leading institute dedicated to healthy aging research. The award recognizes exceptional doctoral researchers whose work demonstrates promise for advancing understanding and treatment of Alzheimer’s Disease (AD) and AD-Related Dementias.

His ongoing project leverages large-scale, multimodal data and foundation model architectures — advanced AI systems trained on vast datasets — to analyze how Alzheimer’s disease progresses. By integrating information from brain imaging, clinical records, and cognitive assessments, the research aims to identify subtle early biomarkers and predict how the disease will develop in individual patients.

“Artificial intelligence offers an opportunity to bridge the complexity of human health data,” Alabi explained. “By combining imaging, genetics, and clinical information, we can uncover hidden patterns that may lead to earlier and more precise interventions for neurodegenerative diseases.” He added that this approach also holds promise for making diagnosis more affordable and accessible, as current methods such as MRI, PET scans, and laboratory biomarker tests are often costly, invasive, and limited in availability, especially in low-resource settings

Foundation models have recently transformed AI fields such as language processing and computer vision. Alabi’s work applies similar methods to biomedical data, using deep learning to uncover connections that traditional statistical models might overlook. The project draws on richly annotated datasets and is expected to contribute to more accurate patient stratification and data-driven decision-making in healthcare.

Experts have noted that the integration of AI with neurological research represents a significant shift in how clinicians and scientists approach complex diseases. Instead of studying one data type in isolation, Alabi’s framework enables the analysis of relationships across different biological and behavioral signals, potentially leading to new diagnostic tools and treatment strategies.

The recognition comes at a time when global health systems are seeking technological approaches to manage the rising prevalence of dementia. Alzheimer’s disease remains the most common form, affecting memory, cognition, and quality of life among older adults. Early detection is crucial, but remains challenging due to the disease’s gradual onset and variability across patients.

As he advances in his academic career, Alabi intends to deepen his focus on AI-driven healthcare innovations and collaborative research aimed at improving the lives of aging populations worldwide.