An ensemble deep learning model for the detection of Oral Squamous Cell Carcinoma (OSCC) using histopathological images. To improve the early detection and diagnosis of oral cancer through advanced image analysis techniques. The basic methods of the convolutional neural network (CNN) and long short-term memory (LSTM) neural network are combine the convolutional neural network (CNN) and long short-term memory (LSTM) neural network to design an open oral scoring model based on CNN + LSTM. An experimental environment is then built to preprocess the data, and finally the model built in this study is trained and simulated. Evaluation metrics demonstrate the effectiveness of the model in diagnosing OSCC with high precision, preprocess the data, offering a potential tool for clinical decision support. Final outcome an oral cancer data analysis based cancer detection for cancer or non-cancer classification.