An MRI-Based Interpretable Deep Learning Model for AD Risk Screening and Progression Prediction

Brisbane Convention & Exhibition Centre 

Alzheimer's disease (AD) is a progressive neurodegenerative disease that poses a significant challenge to global health, profoundly impacting individuals, families, and healthcare systems. Early detection of AD is crucial, as it allows for timely interventions that could slow disease progression and improve patient outcomes. The advent of recent novel immunotherapies has further heightened the need for cost-effective and time-efficient biomarkers for early diagnosis to enhance treatment effectiveness(Hansson, 2021). Deep learning methods has revolutionized MRI's potential towards earlier and more precise AD screening and facilitating timely medical treatment. In addition, interpretable models could enhance the confidence of physicians and patients in medical imaging models.