Deep Learning Algorithm Outperforms Experts in Making Alzheimer’s Diagnosis

Source: The Brink

Alzheimer’s disease is the sixth leading cause of death in the United States. Today, more than five million Americans are living with the neurodegenerative disorder, and that number is predicted to rise to 14 million by 2050. Yet, because different people have different symptoms, it can be hard to get a clear diagnosis of Alzheimer’s disease, and even harder to predict the likelihood that a person will be afflicted by the disease.

Vijaya Kolachalama, a Boston University School of Medicine assistant professor, is making that prediction easier and more certain, with the help of a deep learning algorithm that relies on several indicators, including magnetic resonance imaging (MRI) brain scans, age, gender, and scores on the Mini-Mental State Examination (MMSE), which is commonly used to measure cognitive impairment. The algorithm, described in a paper published in Brain, generates an intuitive visualization of Alzheimer’s risk, leading to accurate diagnosis.

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