We are excited to bring you the latest insights and discoveries from the forefront of ovarian cancer research at the Ovarian Cancer Institute (OCI). Our dedicated team of researchers has been hard at work, and we are thrilled to share some promising updates with you.
Our latest research paper, titled “A personalized probabilistic approach to ovarian cancer diagnostics,” has just been published, and we couldn’t be prouder of the groundbreaking work achieved by our dedicated team.
Here are some key highlights from the paper:
- Predictive models derived from machine learning analyses of serum metabolic profiles can accurately detect ovarian cancer.
- Only a minority of the most predictively informative metabolites is currently annotated (7%)
- Lipids predominate among the most predictively informative metabolites currently annotated
- The frequency distribution of model-derived patient scores were used to develop a clinical tool for the diagnosis of OC
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