|
|
|
| The application value of Bayes′ theorem in diagnostic clinical reasoning training |
| DONG Jiaqiang1 WANG Rui2 ZHANG Wenyao3 |
1.Xijing Hospital of Digestive Diseases, Air Force Medical University State Key Laboratory of Cancer Biology, Shannxi Province, Xi′an 710032, China;
2.Department of Anesthesiology, the First Affiliated Hospital of Xi′an Jiaotong University, Shannxi Province, Xi′an 710061, China;
3.the 10th Squadron of the 3rd Brigade, School of Basic Medicine, Air Force Medical University, Shannxi Province, Xi′an 710032, China |
|
|
|
Abstract Clinical diagnostic thinking is a process of making diagnostic decisions based on the collection and analysis of diagnostic clues. In the traditional teaching of diagnostics, the collection of diagnostic evidence is often emphasized, while the training of diagnostic evidence analysis and diagnosis decision-making is neglected. From the perspective of cognition, diagnostic analysis and decision-making involve complex neuropsychological activities and accumulation of experience, which often have significant individual differences. Therefore, it is of great significance to add the theory teaching of evidence analysis and diagnosis decision formation in diagnosis teaching to improve the training efficiency of diagnosis thinking. This paper analyzes the application value of bayesian statistics in diagnosis analysis and decision making.
|
|
|
|
|
|
[1] 浮豪豪，杨刘刘.基于贝叶斯定理的能源供应网络脆弱性研究[J].统计与决策，2019（16）：35-39.
[2] 邓世广，周龙泉，马亚伟，等.基于贝叶斯定理的地震危险性概率预测研究[J].中国地震，2019，35（1）：1-13.
[3] 孙惠丽，陈维华，刘东朝.基于深度学习的改进贝叶斯网络入侵检测算法[J].软件工程，2019，22（4）：17-20，16.
[4] 杨洋，黄启云，刘追星.基于贝叶斯网络之胃癌的辨证标准研究[J].陕西中医药大学学报，2019，42（2）：119-126.
[5] 黄孟欣，胡玲，张云展，等.中药注射剂联合FOLFOX4化疗方案治疗胃癌的贝叶斯网状Meta分析[J].中药药理与临床 2019，35（1）：160-164.
[6] 张飞飞，周涛，陆惠玲，等.基于贝叶斯粗糙集的肺部肿瘤CT图像高维特征选择算法[J].生物医学工程研究，2018， 37（4）：404-409.
[7] 罗文舒，胡湘，杨卓欣，等.基于MATLAB中风病常用中成药适宜人群的朴素贝叶斯分类器构建[J].山西中医 2018， 34（7）：51-53.
[8] 汤毕书.浅谈贝叶斯定理在疾病诊断中的应用[J].科技与创新，2019（1）：152-153.
[9] Jaynes ET. Probability theory：the logic of science [M]. 3 edn. New York，NY：Cambridge Press；2003.
[10] Kent P，Hancock MJ. Interpretation of dichotomous outcomes：sensitivity，specificity，likelihood ratios，and pre-test and post-test probability [J]. J Physiother，2016，62（4）：231-233.
[11] Ashby D，Smith AF. Evidence-based medicine as Bayesian decision-making [J]. Stat Med，2000，19（23）：3291-3305.
[12] Chen W，Zheng R，Baade PD，et al. Cancer statistics in China，2015 [J]. CA Cancer J Clin，2016，66（2）：115-132.
[13] Song LL，Li YM. Current noninvasive tests for colorectal cancer screening：An overview of colorectal cancer screening tests [J]. World J Gastrointest Oncol，2016，8（11）：793-800.
[14] Kedia S，Das P，Madhusudhan KS，et al. Differentiating Crohn′s disease from intestinal tuberculosis [J]. World J Gastroenterol，2019，25（4）：418-432.
[15] Hall GH. The clinical application of Bayes' theorem [J]. Lancet 1967，2（7515）：555-557.
[16] Hampel H. Genetic counseling and cascade genetic testing in Lynch syndrome [J]. Fam Cancer，2016，15（3）：423-427.
[17] Sinicrope FA. Lynch Syndrome-Associated Colorectal Cancer [J]. N Engl J Med 2018，379（8）：764-773.
[18] Singh S，Resnick KE. Lynch Syndrome and Endometrial Cancer [J]. South Med J，2017，110（4）：265-269.
[19] Lynch HT，Snyder CL，Shaw TG，et al. Milestones of Lynch syndrome：1895-2015 [J]. Nat Rev Cancer，2015，15（3）：181-194.
[20] Usha L，Dewdney SB，Buckingham LE. Tumor Screening and DNA Testing in the Diagnosis of Lynch Syndrome [J]. JAMA，2016，316（1）：93-94.
[21] Elstein AS，Schwartz A. Clinical problem solving and diagnostic decision making：selective review of the cognitive literature [J]. BMJ，2002，324（7339）：729-732.
[22] Herrle SR，Corbett EC Jr，Fagan MJ，et al. Bayes′ theorem and the physical examination：probability assessment and diagnostic decision making [J]. Acad Med，2011，86（5）：618-627.
[23] Gill CJ，Sabin L，Schmid CH. Why clinicians are natural bayesians [J]. BMJ，2005，330（7499）：1080-1083. |
|
|
|
