Development of a prediction model for pancreatic cancer in patients with type 2 diabetes using logistic regression and artificial neural network models.

ASIA unversity > 資訊學院 > 生物資訊與醫學工程學系 > 期刊論文 > Item 310904400/111915

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題名:	Development of a prediction model for pancreatic cancer in patients with type 2 diabetes using logistic regression and artificial neural network models.
作者:	Meng Hsuen Hsieh;Li-Min Sun;Cheng-Li Lin;Meng-Ju Hsieh;Chung-Y Hsu;Chia-Hung Kao
日期:	2018-11
上傳時間:	2019-09-02 06:45:57 (UTC+0)
摘要:	Objectives Patients with type 2 diabetes (T2DM) are suggested to have a higher risk of developing pancreatic cancer. We used two models to predict pancreatic cancer risk among patients with T2DM. Methods The original data used for this investigation were retrieved from the National Health Insurance Research Database of Taiwan. The prediction models included the available possible risk factors for pancreatic cancer. The data were split into training and test sets: 97.5% of the data were used as the training set and 2.5% of the data were used as the test set. Logistic regression (LR) and artificial neural network (ANN) models were implemented using Python (Version 3.7.0). The F1, precision, and recall were compared between the LR and the ANN models. The areas under the receiver operating characteristic (ROC) curves of the prediction models were also compared. Results The metrics used in this study indicated that the LR model more accurately predicted pancreatic cancer than the ANN model. For the LR model, the area under the ROC curve in the prediction of pancreatic cancer was 0.727, indicating a good fit. Conclusion Using this LR model, our results suggested that we could appropriately predict pancreatic cancer risk in patients with T2DM in Taiwan. Keywords: pancreatic cancer, type 2 diabetes, logistic regression, artificial neural network
關聯:	Cancer Management and Research
顯示於類別:	[生物資訊與醫學工程學系 ] 期刊論文

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