To develop a robust and interpretable AI system for ovarian cancer diagnosis using multiclassification techniques and advanced deep learning models, including ResNet152V2, EfficientNetV2B3, and ResNet50V2.
Aim:
The aim of this study is to develop a robust and accurate traffic accident risk prediction model by leveraging deep learning techniques such as CNN (Convolutional Neural Network), BiLSTM (Bi-directional Long Short-Term Memory), and GRU (Gated Recurrent Unit) models.