Binary classification of gynecological cancers based on ATR-FTIR spectroscopy and machine learning using urine samples.

ABSTRACT: Making an early diagnosis of cancer still in the early stages, when completely asymptomatic, is the challenge modern medicine has been setting for several decades. In gynecology, no effective screening has yet been found and approved for endometrial and ovarian cancer. Mammography is an effective screening method for Breast Cancer, as well as Pap Test for Cervical Cancer, but they are underused in third world countries because of their expensive and specific instrumentation. Previous studies showed how "machine learning analysis methods" of the spectral information obtained from dried urine samples could provide good accuracy in differentiation between healthy and ovarian or endometrial cancer. In this study, we also apply ATR-FTIR spectrometry's practical, fast, and relatively inexpensive

SUBMITTER: Vigo F 

PROVIDER: S-EPMC12064457 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature