Trial Parameters
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Brief Summary
This is a multi-center, retrospective clinical study designed to evaluate the application and effectiveness of an AI-assisted predictive model for predicting biological age using electronic health records (EHR). The study will analyze various health data points, including medical history, laboratory results, and clinical observations, to estimate the biological age of patients. By comparing biological age with chronological age, the study aims to assess the accuracy of the model and its potential in identifying age-related health risks and improving patient care.
Eligibility Criteria
Inclusion Criteria: 1. Patients with comprehensive and accessible EHR data, including medical history, laboratory results, treatment data, imaging data (if available), and lifestyle factors (e.g., smoking, physical activity, diet). 2. Patients with no significant cognitive impairments that would prevent them from providing informed consent or participating in the study. 3. All participants must provide informed consent for the use of their medical data for research purposes. Exclusion Criteria: 1. Patients with incomplete or missing critical EHR data such as medical history, laboratory results, or treatment data that are necessary for predicting biological age. 2. atients with severe cognitive disorders (e.g., dementia, significant mental disabilities) who are unable to provide informed consent or participate meaningfully in the study. 3. Patients with terminal illnesses or those with limited life expectancy where biological age predictions may not be relevant for the purposes of the s