For less efficiency and low accuracy of predicting on hypertensive target organ damage， this paper proposes a prediction of hypertensive pulse wave based on mel frequency ceptral coefficient （MFCC）-based feature maps to accomplish the efficient and non-invasive diagnosis on target organ damage. For low accuracy of pulse-taking classification in temporal domain， pulse wave is transformed to the MFCC-based feature maps in frequency domain via replacing angular filter with Gaussian filter， an improved EfficientNet model， EfficientNetS is employed to enhance the ability of global feature extraction via adding the improved SiMAM attention mechanism. The clinical 608 cases of hypertension target organ damage concerning pulse-taking diagnosis are used. The evaluation indicators of five-fold cross-validation classification， i.e. F₁ score， accuracy， precision， sensitivity， area under the curve （AUC）， are 97.31%， 98.72%， 97.71%， 97.04%， 99.13%， respectively. Compared to the typical models， the proposed method has higher classification accuracy and generalization performance. In addition， this paper also studies the correlation between classification of pulse wave and its features， and analyzes the feature importance ranking in temporal domain and frequency domain of pulse-taking， which can help clinicians seek the occurrence mechanisms of hypertension caused by target organ damage， and find the effective measurements for timely prevention and treatment.