A recent research looked for the possibility of using fingerprints as predictors of schizophrenia.
Analysis of fingerprints – artistic interpretation. Image credit: Pixabay, free license
The idea of using fingerprint analysis to determine the risk of schizophrenia is relatively new. The first studies in this field were conducted a few decades ago. However, the research attempts to find connections between fingerprints and mental health issues became more active only in recent years.
One of the possible causes of schizophrenia is prenatal alterations in the development of the central nervous system. As epithelial and neural tissues form together, these alternations can be reflected in fingerprints.
In this latest study, researchers used convolutional neural networks (CNNs) that explicitly take spatial contextual information into account. These networks were fitted to fingerprint images from a large sample, including subjects diagnosed with non-affective psychosis and healthy individuals.
The results indicate that the highest accuracy (70%) was attained by the model that simultaneously used images from the left thumb, index, and middle fingers.
Researchers note that higher accuracy would be hard to achieve as there are multiple causes of schizophrenia. Furthermore, this mental disorder can emerge in different stages of a patients life. But the fingerprint method can be used jointly with genetics or brain imaging data, making fingerprints a useful biomarker for predicting the possible occurrence of the disease.
Source: Fingerprints as Predictors of Schizophrenia: A Deep Learning Study. Schizophrenia Bulletin, sbac173, https://doi.org/10.1093/schbul/sbac173