NewzArtificial intelligence and machine learning models are being utilized to identify individuals at an increased risk of developing various forms of cancer. These computational tools leverage health data that is collected routinely within clinical settings to perform risk assessments.
The application of these technologies represents a potential advancement in preventative oncology by utilizing existing medical records to flag high-risk patients. By analyzing patterns within routine health datasets, these models aim to improve the early detection of cancer susceptibility.
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