Blood test for Aging.AI 3.0 19 parameters
Blood testing for http://www.aging.ai/ version 3.0
These are the 19 biomarkers required to enter into this dashboard:
- Albumin
- Glucose
- Urea (BUN)
- Cholesterol
- Total protein
- Sodium
- Creatinine
- Hemoglobin
- Bilirubin total
- Triglycerides
- HDL Cholesterol
- LDL cholesterol (according to Friedewald)
- Calcium
- Potassium
- Hematocrit
- MCHC (Mean Corpuscular Hemoglobin Concentration).
- MCV (Mean Corpuscular Volume)
- Platelets
- Erythrocytes (RBC).
This blood test can be used to provide insights into human health and aging through the website http://www.aging.ai/
Here is a summary of how this system works:
Entering Blood Results:
Users can enter their blood test results into this system. This includes basic biochemical markers normally found in clinical blood tests.
Analysis and Prediction:
The system uses this data to make predictions about health and aging. The team behind this system specializes in gene expression analysis, biomarker development and drug discovery, especially focused on aging research. The goal is to develop a biomarker that allows users to track changes in their "biological age" and see how different interventions such as diet, exercise and supplements affect it.
Data Use for Research:
All data submitted will be used for research purposes and help train the predictor. Users should be aware that their data cannot be deleted after it is submitted.
Privacy and Security:
The team stresses that since the system uses basic blood biochemistry and does not require personal identification, its use is considered relatively safe.
Mission and Collaboration:
The team's mission is to extend human longevity. They work with academic partners and offer opportunities for sponsorship and research collaboration.
This system seems to offer an innovative way to understand health and potentially improve longevity by using everyday medical data. It emphasizes the importance of knowing your blood biochemistry markers and how this knowledge can be used to improve health-related quality of life.
The "Deep Biomarkers Of Human Aging" Web site offers a system that uses deep neural networks to estimate your biological age based on blood test results. However, it is not designed to predict how old you will become. Instead, it focuses on determining your current biological age, which can be an indication of your overall health and well-being compared to your chronological age. Biological age can differ from chronological age and provide more insight into a person's health status than just age in years. It uses a 21 deep neural networks (DNNs) to predict human biological age. These DNNs have been trained with more than 60,000 blood samples and can predict age with significant accuracy. The research team has also identified five key markers for predicting human age: albumin, glucose, alkaline phosphatase, urea and erythrocytes.
Although the authors of the study are affiliated with Insilico Medicine, Inc. and have potential conflicts of interest, the methodology is considered scientifically valid
see how it works here:
