Unsupervised learning of aging principles from longitudinal data

Biomarkers of age and frailty may aid in understanding the aging process, predicting lifespan or health span and in assessing the effects of anti-aging interventions. Here, the authors show that combining physics-based models and deep learning may enhance understanding of aging from big biomedical d...

Повний опис

Бібліографічні деталі
Автори: Konstantin Avchaciov, Marina P. Antoch, Ekaterina L. Andrianova, Andrei E. Tarkhov, Leonid I. Menshikov, Olga Burmistrova, Andrei V. Gudkov, Peter O. Fedichev
Формат: Стаття
Мова:English
Опубліковано: Nature Portfolio 2022-11-01
Серія:Nature Communications
Онлайн доступ:https://doi.org/10.1038/s41467-022-34051-9