Researchers used machine learning to create personalized "normal" ranges for blood tests, improving diagnostic accuracy. Traditional one-size-fits-all ranges are insufficient; individual set points offer a more precise approach. This personalized approach can aid in early disease detection and risk prediction, paving the way for improved healthcare.
