This study shows that machine learning can accurately distinguish between mito-chondrial and nuclear DNA mutations in primary mitochondrial diseases using only non-ge-netic and non-histological clinical data. While language models underperform in comparison, they show potential as complementary diagnostic tools.
Mutation type prediction in primary mitochondrial diseases using machine learning models applied to non-genetic and non-histological clinical data / Mazzucato, S.; Lopriore, P.; Daddoveri, F.; Lamperti, C.; Carelli, V.; Musumeci, O.; Servidei, S.; Micera, S.; Mancuso, M.; Bandini, A.. - In: RECENTI PROGRESSI IN MEDICINA. - ISSN 0034-1193. - 116:10(2025), pp. 613-614. [10.1701/4573.45801]
Mutation type prediction in primary mitochondrial diseases using machine learning models applied to non-genetic and non-histological clinical data
Bandini A.
2025
Abstract
This study shows that machine learning can accurately distinguish between mito-chondrial and nuclear DNA mutations in primary mitochondrial diseases using only non-ge-netic and non-histological clinical data. While language models underperform in comparison, they show potential as complementary diagnostic tools.
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