Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI)
Pebrianty .
Prodi D3 RMIK Institut Ilmu Kesehatan Bhakti Wiyata Kediri
Computer Science & IT Health Professions Public Health

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
PREDIKSI KETAHANAN HIDUP PASIEN KANKER KOLOREKTAL MENGGUNAKAN JARINGAN SARAF TIRUAN (ARTIFICIAL NEURAL NETWORK) Jerhi Wahyu Fernanda; Pebrianty .; Endah Retnani Wisnaningsih
Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Vol 6, No 1 (2018)
Publisher : Asosiasi Perguruan Tinggi Rekam Medis dan Informasi Kesehatan Indonesia- APTIRMIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33560/.v6i1.185

Abstract

Every cancer patient has hope for good survival, but this often can not be fulfilled due to patient delays in seeking health services. Several studies have shown that the probability of survival of colorectal cancer patients in Indonesia is still below 60%. This study aims to determine the probability of survival of colorectal cancer patients based on comorbidity, clinical stage, age, treatment status, location of cancer, and metastatic history. The study was conducted in five hospitals in Makassar City, with total sampling sampling of 70 colorectal cancer patients diagnosed in 2013. The study design used a retrospective cohort. Data were analyzed using neural network by R software analyzing. The results showed that there was no difference in survival of colorectal cancer patients based on cancer stage variables (pvalue 0.41), comorbidity (pvalue = 0.61), age (pvalue = 0.41), treatment status (pvalue = 0.59) , the location of cancer (pvalue 0.12) whereas in the history of metastatic variables showed no difference in survival among colorectal cancer patients who had a metastatic history with patients without a metastatic history (pvalue 0.028). The results of artificial neural network analysis showed the determinants of survival of colorectal cancer patients are cancer location variables and metastatic history
Co-Authors Endah Retnani Wisnaningsih Jerhi Wahyu Fernanda, Jerhi Wahyu