CT Imaging Of Benign And Malignant Thyroid Tumor To Predict The Depth Of The Learning Algorithm, Built On Circulation Volume Product Thyroid CT Image Neural Network Forecasting Model. To Improved The Prediction Model, Constructed The Convolutional Neural Network Prediction Model And Optimized The Prediction Model. The Detection Is Done By The Single Shot Detection Algorithm. Soc Max Algorithm And L2 Regularization Are Introduced To Prevent The Occurrence Of Over Fitting. This Study Introduces The Technology And Tools Required For The Development Of Forecasting Systems, The Feasibility Analysis Of The System, Demand Analysis And System Design And Other System Development Preliminary Work. IT Describes The Function Of The Thyroid Tumor Prediction System And Related Work Such As System Testing. Based On The Above Research, Thyroid CT Images Obtained By The Cooperative Hospital Are Used As A Data Set, And The Cyclic Convolutional Neural Network Prediction Model Is Used To Predict Training And Testing To The Development Of A Thyroid Tumor Prediction System. The Experimental Results Show That The Prediction System Has High Prediction Accuracy.
