A decision support system based on radiomics and machine learning to predict the risk of malignancy of ovarian masses from transvaginal ultrasonography and serum CA-125.
Valentina ChiappaMatteo InterlenghiGiorgio BoganiChristian SalvatoreFrancesca BertolinaGiuseppe SarpietroMauro SignorelliDominique RonzulliIsabella CastiglioniFrancesco RaspagliesiPublished in: European radiology experimental (2021)
This DSS is a promising tool in women diagnosed with OMs at TUS, allowing to predict the individual risk of malignancy, supporting clinical decision making.
Keyphrases
- contrast enhanced
- machine learning
- decision making
- magnetic resonance imaging
- polycystic ovary syndrome
- magnetic resonance
- artificial intelligence
- lymph node metastasis
- pregnancy outcomes
- deep learning
- big data
- squamous cell carcinoma
- metabolic syndrome
- ultrasound guided
- fine needle aspiration
- type diabetes
- protein kinase
- skeletal muscle
- cervical cancer screening