Survival analysis with the Cox Proportional Hazard Method to determine the factors that affect how long the Large-Scale Social Distancing (LSSD) will applied in various areas affected by the covid-19 pandemic

A, Fauziah A; Budiman, .; Safitri, Defi; Meiza, Asti

doi:10.1088/1742-6596/1751/1/012004

Cited by 4 publications

(4 citation statements)

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“…Tumor grades are indicated using binary values, i.e., zero (0) and one (1) for LGG and HGG, respectively. The ETISTP model employs the CoxPH model [ 34 , 36 , 53 ], which takes into account the tumor volume, tumor grade, age, and GTR status. This integration of different parameters helps to enhance the accuracy of survival time prediction, as will be demonstrated in Section 4 .…”

Section: The Proposed Etistp Modelmentioning

confidence: 99%

“…ETISTP keeps the target value of the survival rate within the range of 0 to 1, where 0 refers to the minimum chances of the patient’s survival and 1 denotes the maximum chances. To compute the probability of a patient’s survival time in terms of days, the ETISTP model uses Equation ( 3 ) [ 53 ], as

where S denotes the survival rate for a certain time t and i represent the time range, e.g.,

is the hazard value obtained from Equation ( 2 ) and

is a derivative for the integration in the equation.…”

Section: The Proposed Etistp Modelmentioning

confidence: 99%

“…ETISTP keeps the target value of the survival rate within the range of 0 to 1, where 0 refers to the minimum chances of the patient's survival and 1 denotes the maximum chances. To compute the probability of a patient's survival time in terms of days, the ETISTP model uses Equation (3) [53], as…”

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confidence: 99%

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ETISTP: An Enhanced Model for Brain Tumor Identification and Survival Time Prediction

et al. 2023

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Technology-assisted diagnosis is increasingly important in healthcare systems. Brain tumors are a leading cause of death worldwide, and treatment plans rely heavily on accurate survival predictions. Gliomas, a type of brain tumor, have particularly high mortality rates and can be further classified as low- or high-grade, making survival prediction challenging. Existing literature provides several survival prediction models that use different parameters, such as patient age, gross total resection status, tumor size, or tumor grade. However, accuracy is often lacking in these models. The use of tumor volume instead of size may improve the accuracy of survival prediction. In response to this need, we propose a novel model, the enhanced brain tumor identification and survival time prediction (ETISTP), which computes tumor volume, classifies it into low- or high-grade glioma, and predicts survival time with greater accuracy. The ETISTP model integrates four parameters: patient age, survival days, gross total resection (GTR) status, and tumor volume. Notably, ETISTP is the first model to employ tumor volume for prediction. Furthermore, our model minimizes the computation time by allowing for parallel execution of tumor volume computation and classification. The simulation results demonstrate that ETISTP outperforms prominent survival prediction models.

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Section: The Proposed Etistp Modelmentioning

confidence: 99%

where S denotes the survival rate for a certain time t and i represent the time range, e.g.,

is the hazard value obtained from Equation ( 2 ) and

is a derivative for the integration in the equation.…”

Section: The Proposed Etistp Modelmentioning

confidence: 99%

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ETISTP: An Enhanced Model for Brain Tumor Identification and Survival Time Prediction

et al. 2023

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“…Model Cox PH d (Kleinbaum dan Klein, 2012). Model semiparametrik Cox PH maupun Cox PH yang diperluas lebih telah banyak digunakan untuk analisis dalam berbagai bidang (Bustan et al, 2018;Fauziah et al, 2021;Husain et al, 2018;Moolgavkar et al, 2018). Selain menggunakan pendekatan nonparametric, untuk menganalisis data survival dapat digunakan pendekatan parametrik.…”

Section: Metodeunclassified

Model Survival Semiparametrik Dan Parametrik Untuk Data Demam Berdarah Dengue (Dbd) Di Rsud Kabupaten Ciamis Tahun 2020

Jajang

Ashfahani

Sb.

et al. 2022

j. sains. teknologi.

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The research is about the best survival analysis model used for patients with Dengue Hemorrhagic Fever (DHF) at Ciamis Hospital in 2020. The purpose of this research is to identify the factors that influence the rate of cure for DHF at Ciamis Hospital in 2020. The method used is survival analysis. Furthermore, the parametric model used Weibull PH, whereas the semiparametric model used Cox PH regression. The result of the analysis showed that the best model obtained was the semiparametric Cox PH regression model, with significant factors including age, Pack Cell Volume (PCV), hemoglobin, White Blood Cell (WBC), and body temperature.

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Parameter estimation of Cox Proportional Hazard regression model with Newton-Raphson

Chrisnawati,

Saputro,

Sutanto

2024

The 3RD INTERNATIONAL CONFERENCE ON NATURAL SCIENCES, MATHEMATICS, APPLICATIONS, RESEARCH, AND TECHNOLOGY (ICON-SMART2022): Mat

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Survival analysis with the Cox Proportional Hazard Method to determine the factors that affect how long the Large-Scale Social Distancing (LSSD) will applied in various areas affected by the covid-19 pandemic

Cited by 4 publications

References 4 publications

ETISTP: An Enhanced Model for Brain Tumor Identification and Survival Time Prediction

ETISTP: An Enhanced Model for Brain Tumor Identification and Survival Time Prediction

Model Survival Semiparametrik Dan Parametrik Untuk Data Demam Berdarah Dengue (Dbd) Di Rsud Kabupaten Ciamis Tahun 2020

Parameter estimation of Cox Proportional Hazard regression model with Newton-Raphson

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