A personalized probabilistic approach to ovarian cancer diagnostics

CONCLUSIONS: An integrative approach using metabolomic profiles and machine learning-based classifiers has been employed to develop a clinical tool that assigns a probability that an individual patient does or does not have ovarian cancer. This personalized/probabilistic approach to cancer diagnostics is more clinically informative and accurate than traditional binary (yes/no) tests and represents a promising new direction in the early detection of ovarian cancer.PMID:38266403 | DOI:10.1016/j.ygyno.2023.12.030

Source: Gynecologic Oncology - January 24, 2024 Category: Cancer & Oncology Authors: Dongjo Ban Stephen N Housley Lilya V Matyunina L DeEtte McDonald Victoria L Bae-Jump Benedict B Benigno Jeffrey Skolnick John F McDonald Source Type: research