Dataset Information

Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.

ABSTRACT:

Background

The current research aimed to develop an artificial intelligence predictive system for individual survival rate of lung adenocarcinoma (LUAD).

Methods

Independent risk variables were identified by multivariate Cox regression. Artificial intelligence predictive system was constructed using three different data mining algorithms.

Results

Stage, PM, chemotherapy, PN, age, PT, sex, and radiation_surgery were determined as risk factors for LUAD patients. For 12-month survival rate in model cohort, concordance indexes of RFS, MTLR, and Cox models were 0.852, 0.821, and 0.835, respectively. For 36-month survival rate in model cohort, concordance indexes of RFS, MTLR, and Cox models were 0.901, 0.864, and 0.862, respectively. For 60-month survival rate in model cohort, concordance indexes of RFS, MTLR, and Cox models were 0.899, 0.874, and 0.866, respectively. The concordance indexes in validation dataset were similar to those in model dataset.

Conclusions

The current study designed an individualized survival predictive system, which could provide individual survival curves using three different artificial intelligence algorithms. This artificial intelligence predictive system could directly convey treatment benefits by comparing individual mortality risk curves under different treatments. This artificial intelligence predictive tool is available at https://zhangzhiqiao11.shinyapps.io/Artificial_Intelligence_Survival_Prediction_System_AI_E1001/.

SUBMITTER: He T

PROVIDER: S-EPMC9123088 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.

He Tingshan T Li Jing J Wang Peng P Zhang Zhiqiao Z

Computational and structural biotechnology journal 20220514

<h4>Background</h4>The current research aimed to develop an artificial intelligence predictive system for individual survival rate of lung adenocarcinoma (LUAD).<h4>Methods</h4>Independent risk variables were identified by multivariate Cox regression. Artificial intelligence predictive system was constructed using three different data mining algorithms.<h4>Results</h4>Stage, PM, chemotherapy, PN, age, PT, sex, and radiation_surgery were determined as risk factors for LUAD patients. For 12-month ...[more]

PMID: 35615023

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Dataset Information

Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.

Background

Methods

Results

Conclusions

Publications

Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.

Similar Datasets

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