Classification of Ovarian Cancer with Multimodal Data Using AI Technology– A Review
P Suma, K V Suma, B P Lakshmishree, Mangala Gouri S R · 2024
One of the main causes of carcinoma includes ovarian epithelial cells. To monitor the ovarian cancer., there are number of approaches such as biomarkers., ultrasound scan., Histopathology., CT scan etc. Artificial Intelligence (AI) contributes a important function in the area of medical sciences that operates on different modalities and helps the doctor to provide timely treatment. Deep learning models are operative to integrate different modalities which help to upsurge the accuracy for both diagnosis and prognosis. AI models are also proficient to notice the pattern which describes patient responses towards the treatment. In this work deep learning architecture are incorporated for accurate and initial finding of the cancer by integration multiple modalities such as biomarkers and histopathological images. Algorithms for machine learning work well in differentiating between patients with aggressive and benign ovarian cancer. Statistical analysis can be accomplished to compute the risk factor and the survival period of the patient. So by these techniques it is helpful to notice the epithelial ovarian cancer at early stage before it spreads to other organs.