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Data classification is an important data mining role in biomedicine. This paper proposes a method to analyze colorectal carcinoma auto-fluorescence spectrogram data based on counting kNN algorithm after analyzing the characteristics of biomedicine data. Though counting kNN algorithm for classification is simple and effective, it doesn't deal with biomedicine data well. After analyzing the algorithm performance, a novel counting kNN algorithm by index tree is presented. The new method improves the efficiency by using a tree structure index with the same accuracy. Experiments show that this method outperforms the distance-based voting kNN for accuracy, and ckNN for efficiency.