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Mount Sinai Developed the HistoAge Model, an Algorithm that can Predict Age at Death

HistoAge model offers a more rigorous, unbiased, and robust metric of cellular changes underlying degenerative diseases.

Researchers at Mount Sinai Hospital have developed an algorithm called the HistoAge Model, which can predict age at death and assess neurodegeneration. 

Mount Sinai researchers trained a machine learning model with almost 700 digitalized images of human hippocampal from aged brain donors to develop the histological brain age estimation algorithm to predict a person’s age at death.  

The research focused on the hippocampal region, as the hippocampus is involved in both brain aging and age-related neurodegenerative disorders. 

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Age acceleration based on HistoAge exhibits robust correlations with cognitive impairment, cerebrovascular disease, and the aggregation of Alzheimer’s-related proteins, surpassing existing age acceleration metrics such as DNA methylation.

According to researchers, the HistoAge model, with other subsequent similar algorithms, introduces a fresh paradigm for evaluating aging and neurodegeneration in human samples, with seamless scalability for implementation in clinical and translational research facilities. Moreover, this methodology offers a more rigorous, unbiased, and robust metric of cellular changes underlying degenerative diseases.

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Boudhayan Ghosh
Boudhayan Ghosh
I am a Journalism and Communication graduate, currently working with Analytics Drift as an Associate Technology Journalist. My other hobbies include consuming art and watching football.

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