InBody_Scan_Dataset

The dataset contains detailed body composition profiling of 4,328 individuals as done by the InBody770, a certified medical body composition analyzer. The 131 records with 231 parameters cover a broad variety of physiological metrics such as total and segmental water contents, muscle contents, fat content, visceral fat area, percentages of body fat, and some important derived ratios like ECW/TBW and SMM/Weight. The data was downloaded from the internal hard disk of InBody770 directly in the standardized PDF form to offer utmost standard uniformity and accuracy for every entry. After automated conversion and cleaning steps, the data were organized into machine learning-ready format with separate sets of features: demographics, anthropometric, body composition, and metabolic risk indicators. High-resolution data offers the construction of predictive models for metabolic health risk and allows for stratified analyses based on gender, age, and BMI. Given the sheer size, granularity, and standardization of the dataset, it becomes a quintessential research instrument in support of preventive healthcare, digital biomarker discovery, and AI-assisted health risk classification.