| Data mining, it is processes that like taking effective, original, and potential serviceable the last comprehensible model form mass data. The broad definition of data mining is a process that to dig interesting intellective from the mass data to deposit database, data warehouse and other information bank. The other name is regard the data mining as a basic step that knowledge discovery from the database, knowledge discovery's process have seven steps to make up: (1) data purging (2) data integration (3) data selection (4) data covert (5) data mining (6) mode evaluation (7) knowledge representation. Data mining can together with consumer or knowledge base alternately.Data mining to utilize some areas' thoughts as follow:(1) from statistician's sampling estimation and hypothesis testing (2) artificial intelligence, pattern recognition and machine learning's search algorithm, modeling technique and theory of learning. Data mining accept fleetly from other areas thoughts. These areas contain optimization, evolutionary computing, information theory, signal processing, visualization and information retrieval. Some other areas are playing important prop up support role. Extraordinarily, to demand database provide effective memory, indexes and query processing support. Originate from high performance calculating technique which to deal with mass data is very important. Distributed technology can help to deal with mass data, and when the data can't concentration together to deal with that is more important.Information technology and Bioscience are known as 21 century's signal subject. This century's human society is reputation "information society", information-based, networking, high-technology have already to become society development's fundamental characteristics. Especially 20 century 90 eras, Such as Internet the modern time information technology's progress at full speed and human genome project accomplish. People to be faced with not only are enormous information data, but also vast information oceans. Just to connect Biotechnology with information technology, Catalysis is a new branch of study Laboratory Medical Informatics has birth.Medicine is a science that a trial and the information to integrate very tightly, Laboratory Medicine is not exception. Accomplish a diagnosis or therapeutics'process i.e. information acquisition, Handling and utilization's process. By means of obtain in information more widely, analyze information more science, and utilize information more reasonably to decide the Medical treatment quality and Medical treatment level, and computer technology play a very important role in it. Because of computer technology make Laboratory Medicine to take place revolution change. Changed Laboratory Medicine's learning philosophy and work style. With the information technology develops, Principal gene library and protein information utilize. Height integrated laboratory information system and Hospital Information System are built. Clinical Medicine informatics and disease informatics in high speed developed, the direction of Laboratory Medicine educative to adapt a new style. In all Laboratory colleagues strive in common. Laboratory Medicine also developed quickly that not only to offer experimental data for clinical, but also to offer very important information for clinical to diagnose and treatment.To make the limited laboratory information extraction for efficient diagnosis and treatment of information, and to explore a clinical new way for laboratory medicine from a technical level.CA72-4, CA199, and CEA, the three blood serum makers are used to diagnose carcinoma of large intestine, for example, relying on laboratory information system (LIS) and hospital information system (HIS) data information platform, artificial neural network (ANN) is used for data digging tools,and by means of SPSS statistical software to build ROC data sets, Depend on posterior probability to comment gastrointestinal tumor markers in each inspection reports.In 1206 samples, gastrointestinal tumor marker test specimens of colorectal cancer is accounted for 11.25%, to build CA199, CA72-4 and CEA testing,seeking and diagnosis carcinoma of large intestine of ROC data sets; the three carcinoma of large intestine serum markers'concentrations are significantly higher than the healthy control group and the other disease groups (P<0.01); CA199, CA72-4, CEA, and artificial neural network diagnostic model for carcinoma of large intestine screening predictive value of area under the ROC curve are 0.624,0.692,0.721and 0.785,while the diagnosis of carcinoma of large intestine in the area under the ROC curve are 0.607,0.762,0.687 and 0.795.Respectively, survey report assigned test posterior probability objectively provides a reference value.ANN model has a higher diagnostic efficiency analysis in a number of test items, to build ROC data sets,and a inspection report satisfied with the ROC data sets,which has been given the posterior probability,is a feasible new way in clinical practice of laboratory medicine.
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