| Summary: | 碩士 === 元智大學 === 資訊管理學系 === 100 === This research tracks back and uses among 2004-2010 years, in the electronic charts of one medical information system of teaching hospital in Taoyuan, all is in hospital day and death day for the last time, the interval of two is less than or equal to 30 days in hospital, check the data as inputting changing one in the laboratory of patient's component, and use the materials to classify technological C4.5, C&;RT, SVM and NN, etc., development build construct to a short-term survive prediction model of terminal stage. Research compares the accuracy and precision of every group of models, in non-cancer patient's group with NN, C&;RT, C5.0, while combining cancer and non predicting with C5.0 categorised technology by cancer patient's groups, predict the accuracy can be more than 90%; Categorised technology (90.22%) of the decision tree at the same time Survive prediction of time apply will it be 30 day such as inpatient terminal stage to, accuracy superior to kinds of neural network (88.93%) on average And support vector machine (88.03%) . In the attribute sensitivity analysis result, patient in second and third weeks, examine Albumin, third weeks examine CRP, have indicator nature meanings on the surviving probability within predicting its 30 days. After the patient moves in the hospital, its regular general blood and biochemistry examining value that carry out can find the patient with terminal stage the time of surviving has apparent concerned withing nature in a short time, can utilize clinical medical the intersection of routine inspection and homework can get, write into materials, enter, predict way and changing useful information and knowledge into effective automatically, can assist clinical staff members, patient's surviving probability and time after moving in this time in early inference terminal stage correctly, in order to be regarded as medical treatment to support the favorable tool of decision while looking after. Expect this result of study besides can offer clinical staff member's useful information ing, can also stimulate government and medical policy leader out to the attention in relevant topics such as looking after and approaching one's end of life care in terminal stage.
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