췌장암 조기진단을 위한 조건부 확률 기반 지능형 진단 방식
Intelligent Diagnosing Method Based on the Conditional Probability for the Pancreatic Cancer Early Detection
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Early diagnosis of pancreatic cancer had been considered one of the important barrier for successful therapy since the five year survival rate after treatment of pancreatic cancer was critically low. Nonetheless, patients often miss the golden time of treatment because they rarely visit the hospital until their symptoms are severe. To overcome these problems, a lot of information about the patient’s symptoms should be applied as biomarkers for early diagnosis. For this reason, a biomarker for early detection of pancreatic cancer (CA19-9) has been developed as a diagnostic kit. However, since the diagnosis is not accurate enough, pancreatic symptoms (abdominal pain, jaundice, anorexia, diabetes, etc.) and biomarkers (CA19-9) should be considered together. We develop an intelligent diagnostic system that considers CA19-9 and the incidence of pancreatic cancer for pancreatic symptoms that was determined by studying a large number of patient information. It shows a higher accuracy than one using CA19-9 alone. It may increase the survival rate of pancreatic cancer because it can diagnose pancreatic cancer early.
Abstract
Early diagnosis of pancreatic cancer had been considered one of the important barrier for successful therapy since the five year survival rate after treatment of pancreatic cancer was critically low. Nonetheless, patients often miss the golden time of treatment because they rarely visit the hospital until their symptoms are severe. To overcome these problems, a lot of information about the patient’s symptoms should be applied as biomarkers for early diagnosis. For this reason, a biomarker for early detection of pancreatic cancer (CA19-9) has been developed as a diagnostic kit. However, since the diagnosis is not accurate enough, pancreatic symptoms (abdominal pain, jaundice, anorexia, diabetes, etc.) and biomarkers (CA19-9) should be considered together. We develop an intelligent diagnostic system that considers CA19-9 and the incidence of pancreatic cancer for pancreatic symptoms that was determined by studying a large number of patient information. It shows a higher accuracy than one using CA19-9 alone. It may increase the survival rate of pancreatic cancer because it can diagnose pancreatic cancer early.
참고문헌 (10)
- A.K. Sarnecka, "An Overview of Genetic Changes and Risk of Pancreatic Ductal Adenocarcinoma", Journal of Cancer, 7(14), pp.2045~2051 (2016)
- M. Wahutu, "Pancreatic Cancer : A Survival Analysis Study in Oklahoma", Journal of Oklahoma State Medical Association, 109(7-8), pp.391~398 (2016)
- S. Ngamruengphong, "Screening for Pancreatic Cancer", Surgical clinics of North America, 96, pp.1223~1233 (2016)
- A.Mohamed, "Can Serum ICAM1 distinguish pancreatic cancer from chronic pancreatitis", Asian Pacific Journal of Cancer Prevention, 17(10), pp.4671~4675
- G. Ge, "Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles", BMC Bioinformatics, 9, pp.275~ (2008)
- F. Gorunescu, "Competitive collaborative neural computing system for medical diagnosis in pancreatic cancer detection", Biological Journal of the Linnean Society, 28(1), pp.33~ (2011)
- F.T. Dombal, "Computer-aided diagnosis of acute abdominal pain", British Medical Joural, 2, pp.9~13 (1972)
- A. Alvaro-Meca, "In-Hospital Death Caused by Pancreatic Cancer in Spain : Applicatioin with Bayesian Network", International Journal of Biomedical Science, 7(2), pp.125~130 (2011)
- L. You, "Analysis of clinical characteristics and treatment of pancreatic cystic tumors", Chinese Journal of Cancer Research, 28(5), pp.519~527 (2016)
- A. Engebretson, "Patient and caregiver awareness of pancreatic cancer treatments and clinical trials", Journal of Gastrointestinal Oncology, 7(2), pp.228~233 (2015)