Objective To investigate the expressions of COX-2 and VEGF-C in breast carcinoma and their correlation with lymphangiogenesis and lymph node metastasis. Methods The expressions of COX-2 and VEGF-C and D2-40 were evaluated in 46 cases of breast carcinoma by immunohistochemical staining SP methods. The lymphatic vessels density (LVD) in tumor was counted through the special marker D2-40. Results The positive rate of COX-2 and of VEGF-C was 73.91% (34/46) and 71.74% (33/46) respectively in breast carcinoma tissues. The positive rate of COX-2 and VEGF-C was 86.48% (32/37) and 81.08% (30/37), and LVD was (13.350?3.097)/?200 in the lymph node metastasis group, while that in non-lymph-node metastasis group was 22.22% (2/9), 33.33% (3/9) and (9.560?2.031)/?200 respectively, with significant difference between the two groups (P

Objective To develop a real-time QRS complex detection algorithm of dynamic ECG signals for the GPRS mobile telemonitoring system. Methods Before the first and second derivatives of ambulatory ECG signals were processed by moving average method, the signals sampled from CM5 monitoring lead were filtered with the average of continuous four ECG sample signal points. The R waves could be detected precisely by local minima of second derivatives and Q & S waves were located correctly by cross-zero points of first derivatives of ambulatory ECG signals in a short-time searching windows. The QRS recognition thresholds, which could revise themselves according to the detected values and vary with the analyzing signals, were designed in this paper. Results With a polynomial computation complexity, the novel algorithm insensitive to baseline draft and noise caused by mobile communication filtered power-line interference and most of muscle noise and reduced the search time below 0.02 s during detecting each Q wave, R wave and S wave. For the normal and clinical patients, this algorithm correctly detected up to 99.8% of the QRS complex of ambulatory ECG signals. Conclusion The algorithm can meet the need of real-time QRS complex detection and analysis for the GRRS mobile ECG telemonitoring system.

Modern medicine generates a great deal of information stored in the medical database. Extracting useful knowledge and providing scientific decision-making for the diagnosis and treatment of disease from the database increasingly becomes necessary. Data mining in medicine can deal with this problem. It can also improve the management level of hospital information and promote the development of telemedicine and community medicine. Because the medical information is characteristic of redundancy, multi-attribution, incompletion and closely related with time, medical data mining differs from other one. In this paper we have discussed the key techniques of medical data mining involving pretreatment of medical data, fusion of different pattern and resource, fast and robust mining algorithms and reliability of mining results. The methods and applications of medical data mining based on computation intelligence such as artificial neural network, fuzzy system, evolutionary algorithms, rough set, and support vector machine have been introduced. The features and problems in data mining are summarized in the last section.
Algorithms ; Automatic Data Processing ; Databases, Factual ; Decision Making, Computer-Assisted ; Decision Trees ; Fuzzy Logic ; Information Storage and Retrieval ; methods ; Neural Networks (Computer)