Predicting the progression of amnestic mild cognitive impairment (aMCI) to Alzheimer disease (AD) is of paramount significance in initiating mechanistic therapies. However, there lacks specific consensus on the use of various prognosticating factors for the disease progression. Now, a recent study published in the Journal of Alzheimer’s Disease substantiates the effectiveness of the interpretation of data obtained from diverse and heterogeneous sources using artificial neural networks (ANNs) in predicting the disease conversion.

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