Advanced artificial intelligence models are making significant strides in oncology by predicting patient outcomes and treatment toxicities across cancer types. Using transformer models with ^18F-FDG PET imaging, researchers have improved overall survival prognosis predictions in cervical cancer. Separately, interpretable machine learning integrating radiomic and dosimetric data predicts hematologic toxicity during cervical cancer chemoradiotherapy. These tools promise to refine personalized cancer care and optimize therapeutic regimens.