Integrative adaptive indexes from noisy routine haematological markers can predict and discriminate health status and biological age

Common haematological markers can reliably predict individual chronological age and health status.

• The analysis utilized both synthetic and real retrospective patient data, incorporating medically relevant and extreme cases.
• Machine intelligence was combined with explainable risk assessment scores to identify clinically significant patterns.
• Testing was conducted on the US CDC NHANES database with 100,000 participants and validated using the UK Biobank with 500,000 participants.
• Despite challenges from self-reporting and sparse data in these databases, the findings remained statistically significant.
• This approach may provide rapid and scalable implementations for personalised healthcare without the need for specialized tests.

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