Web Based Fuzzy Expert System for Lung Cancer Diagnosis

被引：0

作者：

Rodiah ^{[1
]}

Fitrianingsih ^{[1
]}

Susanto, Herio ^{[1
]}

Haryatmi, Emy ^{[2
]}

机构：

[1] Gunadarma Univ, Dept Informat, Depok, Indonesia

[2] Gunadarma Univ, Dept Technol & Engn, Depok, Indonesia

来源：

PROCEEDINGS OF 2016 2ND INTERNATIONAL CONFERENCE ON SCIENCE IN INFORMATION TECHNOLOGY (ICSITECH) - INFORMATION SCIENCE FOR GREEN SOCIETY AND ENVIRONMENT | 2016年

关键词：

doubling time; fuzzy sugeno; performance status; lung cancer;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Currently, cancer is a leading cause of death worldwide. One of the most common causes of cancer death are lung cancer. We implemented a lung cancer detection using Sugeno Fuzzy Logic method. We use PHP to construct a website based of an expert system and MySQL for our database collection. The source of our data used to build the expert system are collected from many literature studies related to medical books and interviews with the doctors or physicians to assemble 5 different variables that we use as input. The variables are anamnesis, doubling time, the degree of the smokers, age and performance status. The result of expert system's diagnoses produce three assumptions, (i) no tumor is indicated, (ii) tumor is indicated but benign and (iii) malignant tumors are indicated. The designs of this system are expected to help doctors and physicians to aid them in making a diagnosis of lung cancer.

引用

页码：142 / 146

页数：5

共 11 条

[1]

[Anonymous], 2012, Estimated Cancer Incidence, Mortality and Prevalence Worldwide in 2012

[2]

[Anonymous], 2015, CANC FACTS FIG 2015

[3]

ARAI T, 1994, JPN J CLIN ONCOL, V24, P199

[4]

Atiyeh H., 2013, MASS DETECTION LUNG