ABSTRACT
Objective To evaluate the diagnostic value of thinprep cytologic test (TCT) combined with high-risk human papillomavirus (HR-HPV) DNA for cervical cancer (CC). Methods 141 cases of patients with abnormal cervical lesions were abnormal examined by TCT and were graded by the results of TCT and cervical biopsy, the HR-HPV-DNA was detected by surface plasmon resonance (SPR). Results The cervical biopsy positive rate 65.2% (92/141) was significantly higher than the positive rate of TCT 39.0% (55/141) (χ2=19.45, P < 0.05). The positive rate of HR-HPV-DNA was 66.0% (93/141) was significantly higher than the positive rate of TCT 39.0% (55/141), (χ2=20.53, P < 0.05). Conclusion TCT, HR-HPV-DNA and cervical biopsy are important clinical diagnostic methods for cervical lesions, combine detection of TCT and HR-HPV-DNA can improve the detection rate of cervical lesions.
ABSTRACT
The performance of an electroencephalography (EEG) automatic detection and classification system mainly depends on the feature extraction of EEG signal. This paper analyses the advantages and disadvantages of the current EEG feature extraction methods, and then presents a new EEG feature extraction method based on echo state networks (ESN). The new method is a nonlinear method, and can extract the EEG features reversibly. Therefore, the information lost in the process of feature extraction is much less than that of the traditional EEG. Additionally, the realization of this method just needs to compute the pseudo inverse of a matrix, which keeps it efficient. Experimental results have showed that the new method could well accomplish the task of automatic detection and classification of EEG signals.