According to the WHO, every two minutes there is one patient who died from cervical cancer. The high mortality rate is due to the lack of awareness of women for early detection. There are several factors that supposedly influence the survival of cervical cancer patients, including age, anemia status, stage, type of treatment, complications and secondary disease. This study wants to classify/predict cervical cancer survival based on those factors. Various classifications methods: classification and regression tree (CART), smooth support vector machine (SSVM), three order spline SSVM (TSSVM) were used. Since the data of cervical cancer are imbalanced, synthetic minority oversampling technique (SMOTE) is used for handling imbalanced dataset. Performances of these methods are evaluated using accuracy, sensitivity and specificity. Results of this study show that balancing data using SMOTE as preprocessing can improve performance of classification. The SMOTE-SSVM method provided better result than SMOTE-TSSVM and SMOTE-CART.
Skip Nav Destination
,
,
,
,
Article navigation
6 April 2016
SYMPOSIUM ON BIOMATHEMATICS (SYMOMATH 2015)
4–6 November 2015
Bandung, Indonesia
Research Article|
April 06 2016
Cervical cancer survival prediction using hybrid of SMOTE, CART and smooth support vector machine
S. W. Purnami;
S. W. Purnami
a
1Department of Statistics,
Institut Teknologi Sepuluh Nopember
, Surabaya, Indonesia
Search for other works by this author on:
P. M. Khasanah;
P. M. Khasanah
b
2Faculty of Medicine,
Prince Songkla University
, Thailand
Search for other works by this author on:
S. H. Sumartini;
S. H. Sumartini
c
3Department of Statistics,
Institut Teknologi Sepuluh Nopember
, Surabaya, Indonesia
Search for other works by this author on:
V. Chosuvivatwong;
V. Chosuvivatwong
2Faculty of Medicine,
Prince Songkla University
, Thailand
Search for other works by this author on:
H. Sriplung
H. Sriplung
2Faculty of Medicine,
Prince Songkla University
, Thailand
Search for other works by this author on:
S. W. Purnami
1-1,a
P. M. Khasanah
2,b
S. H. Sumartini
1-3,c
V. Chosuvivatwong
2
H. Sriplung
2
1Department of Statistics,
Institut Teknologi Sepuluh Nopember
, Surabaya, Indonesia
2Faculty of Medicine,
Prince Songkla University
, Thailand
3Department of Statistics,
Institut Teknologi Sepuluh Nopember
, Surabaya, Indonesia
AIP Conf. Proc. 1723, 030017 (2016)
Citation
S. W. Purnami, P. M. Khasanah, S. H. Sumartini, V. Chosuvivatwong, H. Sriplung; Cervical cancer survival prediction using hybrid of SMOTE, CART and smooth support vector machine. AIP Conf. Proc. 6 April 2016; 1723 (1): 030017. https://doi.org/10.1063/1.4945075
Download citation file:
Pay-Per-View Access
$40.00
Sign In
You could not be signed in. Please check your credentials and make sure you have an active account and try again.
Citing articles via
The implementation of reflective assessment using Gibbs’ reflective cycle in assessing students’ writing skill
Lala Nurlatifah, Pupung Purnawarman, et al.
Inkjet- and flextrail-printing of silicon polymer-based inks for local passivating contacts
Zohreh Kiaee, Andreas Lösel, et al.
Effect of coupling agent type on the self-cleaning and anti-reflective behaviour of advance nanocoating for PV panels application
Taha Tareq Mohammed, Hadia Kadhim Judran, et al.
Related Content
Smooth support vector machine based on polynomial function for depression detection using electroencephalogram (EEG) signal
AIP Conf. Proc. (November 2024)
IoT based heart disease prediction using smote and machine learning techniques
AIP Conf. Proc. (November 2023)
Heart disease prediction system using (SMOTE technique) balanced dataset and decision tree classifier
AIP Conf. Proc. (December 2023)
Survival analysis of cervical cancer using stratified Cox regression
AIP Conf. Proc. (April 2016)
The potential impact of gender and smoking-onset age on myocardial infarction
AIP Conf. Proc. (December 2022)