From single-visit to multi-visit image-based models: single-visit models are enough to predict obstructive hydronephrosis

Stanley Bryan Z. Hua; Mandy Rickard; John Weaver; Alice Xiang; Daniel Alvarez; Kyla N. Velear; Kunj Sheth; Gregory E. Tasian; Armando J. Lorenzo; Anna Goldenberg; Lauren Erdman

doi:10.1117/12.2670148

6 March 2023 From single-visit to multi-visit image-based models: single-visit models are enough to predict obstructive hydronephrosis

Stanley Bryan Z. Hua, Mandy Rickard, John Weaver, Alice Xiang, Daniel Alvarez, Kyla N. Velear, Kunj Sheth, Gregory E. Tasian, Armando J. Lorenzo, Anna Goldenberg, Lauren Erdman

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Proceedings Volume 12567, 18th International Symposium on Medical Information Processing and Analysis; 1256710 (2023) https://doi.org/10.1117/12.2670148
Event: 18th International Symposium on Medical Information Processing and Analysis, 2022, Valparaíso, Chile

Abstract

Previous work has shown the potential of deep learning to predict renal obstruction using kidney ultrasound images. However, these image-based classifiers have been trained with the goal of single-visit inference in mind. We compare methods from video action recognition (i.e. convolutional pooling, LSTM, TSM) to adapt single-visit convolutional models to handle multiple visit inference. We demonstrate that incorporating images from a patient’s past hospital visits provides only a small benefit for the prediction of obstructive hydronephrosis. Therefore, inclusion of prior ultrasounds is beneficial but prediction based on the latest ultrasound is sufficient for patient risk stratification.

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Stanley Bryan Z. Hua, Mandy Rickard, John Weaver, Alice Xiang, Daniel Alvarez, Kyla N. Velear, Kunj Sheth, Gregory E. Tasian, Armando J. Lorenzo, Anna Goldenberg, and Lauren Erdman "From single-visit to multi-visit image-based models: single-visit models are enough to predict obstructive hydronephrosis", Proc. SPIE 12567, 18th International Symposium on Medical Information Processing and Analysis, 1256710 (6 March 2023); https://doi.org/10.1117/12.2670148

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KEYWORDS

Ultrasonography

Data modeling

Education and training

Performance modeling

Kidney

Feature extraction

Modeling

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