New Delhi: Predicting longevity, as to how many years will a person live is now possible with Artificial Intelligence.
Yes, you've heard it right.
Precision radiology is the new thing which makes use of feature engineering and deep learning methods in a radiomics framework to predict the age of a person.
The concept has approached on obtaining precise knowledge of the true state of health of an individual, which results from a combination of their genetic factors and exposure to environment.
Currently, this concept is limited by lack of effective non-invasive medical tests to define the full range of phenotypic variation associated with individual health.
Experts working on this have presented proof of experiments to show how routinely acquired cross-sectional CT imaging may be used to predict patient longevity as a proxy for overall individual health and disease status using computer image analysis techniques.
Despite limited options, the results see more productivity as compared to the previous manual clinical methods for predicting life accuracy.
This work shows that radiomics techniques can be used to extract biomarkers relevant to one of the most widely used outcomes in epidemiological and clinical research – mortality, and that deep learning with convolutional neural networks can be usefully applied to radiomics research.