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Biological Age: Difference between revisions
→Biological Age Estimation Methods
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* '''Hochschild’s Method''' differs from MLR and PCA by making chronological age an independent variable. It aims to estimate biological age by adjusting chronological age based on specific biomarkers. | * '''Hochschild’s Method''' differs from MLR and PCA by making chronological age an independent variable. It aims to estimate biological age by adjusting chronological age based on specific biomarkers. | ||
* '''Klemera and Doubal’s Method (KDM)''' shares a similar concept with Hochschild’s method but uses a more complex statistical approach. It treats chronological age as an independent variable and incorporates multiple biomarkers to estimate biological age. | * '''Klemera and Doubal’s Method (KDM)''' shares a similar concept with Hochschild’s method but uses a more complex statistical approach. It treats chronological age as an independent variable and incorporates multiple biomarkers to estimate biological age. | ||
* '''Deep Learning'''-based approaches represent an emerging and powerful method for biological age estimation. Leveraging complex neural network architectures, these methods can analyze large datasets of biomarkers, integrating diverse types of biological data. Deep learning models can uncover intricate patterns in the data that may be missed by traditional statistical techniques, offering potentially more accurate and personalized biological age estimations. However, they require large, well-curated datasets to be effective. | |||
=== Role of Chronological Age === | === Role of Chronological Age === | ||