Supplemental Figure 3 from Utilizing Serum-Derived Lipidomics with Protein Biomarkers and Machine Learning for Early Detection of Ovarian Cancer in the Symptomatic Population

Key Points

Machine learning successfully identifies gangliosides for early-stage ovarian cancer detection.
Top 50 gangliosides were evaluated using ANOVA, highlighting significant differences between control and cancer groups.
The approach utilized PLSDA to analyze lipidomic data for effective differentiation in detection.
These findings support the potential of lipidomics as a promising biomarker for early ovarian cancer screening.

Analysis using machine learning identifies gangliosides in ovarian cancer, implying potential for early screening.

Supplemental Figure 3. Cohort 2 PLSDA and heatmaps of top 50 gangliosides by ANOVA comparing controls to OC and early-stage OC

No takes yet. Share an insight, caveat, or question.

Giles et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark

Share