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2021 World Conference on Lung Cancer (Posters)
FP08. Artificial Neural Network-Based Tumour Recur ...
FP08. Artificial Neural Network-Based Tumour Recurrence Prediction in Non-Small Cell Lung Cancer Patients Following Radical Radiotherapy
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Video Summary
The presenter discussed using an artificial neural network (ANN) to predict tumor occurrence in non-small cell lung cancer patients receiving radical radiotherapy. The study used 451 patients for training and testing the network. The ANN outperformed classical logistic regression, with consistent accuracy, precision, sensitivity, specificity, and F1 scores above 70%. Reproducibility was assessed using Monte Carlo cross-validation, and the ANN demonstrated excellent ability to distinguish between dependent and independent variables. The presenter concluded that deep learning with ANN is a promising approach for predicting tumor recurrence and further testing in independent datasets is warranted.
Asset Subtitle
Timothy Mitchell
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Speaker
Timothy Mitchell
Topic
Multimodality of Advanced Lung Cancer
Keywords
artificial neural network
tumor occurrence
non-small cell lung cancer
radical radiotherapy
predict
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