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말기 대장암환자에서 중상을 통한 예후 측정 및 증상조절
이도행,최윤선,홍명호,김준석,이경진,김영수,Lee, Do-Haeng,Choi, Youn-Seon,Hong, Myung-Ho,Kim, Jun-Suk,Lee, Kyung-Jin,Kim, Young-Soo 한국호스피스완화의료학회 1999 한국호스피스.완화의료학회지 Vol.2 No.2
Accurately estimating survival times in terminal cancer patients is very difficult for palliative care clinicians. But a reasonably accurate estimate of survival would permit the medical team to : Plan the ideal therapeutic strategy between overtreatment and too early discontinuation of specific therapy. Answer any questions asked by the patient or family. Organize adequate assistance for the patient concerned. Decide on the eligibility of the patient for clinical trials and whether to begin a treatment, the effects of which will not be immediate. This case was a 79 year-old male patient with colon cancer. He complained of dry mouth, anorexia, weight loss and showed KPS $40{\sim}50$ on admission day. 40 days later he died. To improve patient/family quality of life, it is necessary to improve the ability to estimate accurately a patient's length of survival.
변형된 샤논 엔트로피식을 이용한 온실가스 농도변화량 예측
김상목 ( Sang Mok Kim ),이도행 ( Do Haeng Lee ),최얼 ( Eol Choi ),고미솔 ( Mi Sol Koh ),양재규 ( Jae Kyu Yang ) 한국환경과학회 2013 한국환경과학회지 Vol.22 No.11
Entropy is a measure of disorder or uncertainty. This terminology is qualitatively used in the understanding of its correlation to pollution in the environmental area. In this research, three different entropies were defined and characterized in order to quantify the qualitative entropy previously used in the environmental science. We are dealing with newly defined distinct entropies E1, E2, and E3 originated from Shannon entropy in the information theory, reflecting concentration of three major green house gases CO2, N2O and CH4 represented as the probability variables. First, E1 is to evaluate the total amount of entropy from concentration difference of each green house gas with respect to three periods, due to industrial revolution, post-industrial revolution, and information revolution, respectively. Next, E2 is to evaluate the entropy reflecting the increasing of the logarithm base along with the accumulated time unit. Lastly, E3 is to evaluate the entropy with a fixed logarithm base by 2 depending on the time. Analytical results are as follows. E1 shows the degree of prediction reliability with respect to variation of green house gases. As E1 increased, the concentration variation becomes stabilized, so that it follows from linear correlation. E2 is a valid indicator for the mutual comparison of those green house gases. Although E3 locally varies within specific periods, it eventually follows a logarithmic curve like a similar pattern observed in thermodynamic entropy.