Nancy F. YuanUniversity of California, United States of America
Title: Shallow Convolutional Neural Network for Real-Time COVID-19 Pneumonia Detection
The prevalence of COVID-19 has placed undue burden on the healthcare system, signaling a critical need to develop innovative machine learning (ML) strategies to improve triage and care for patients who are hospitalized with COVID-19. Recent developments in artificial intelligence have shown that deep learning algorithms such as convolutional neural networks (CNN) are effective in automating various tasks in medical imaging such as pneumonia detection . The challenge remains in implementing these algorithms efficiently in the clinic where there may be insufficient hardware to support CNN with hundreds of hidden layers and millions of parameters . To address this challenge, we developed a shallow 3-layer CNN classifier, SimplePNUnet, to detect the presence of pneumonia using a subset of 2000 frontal chest X-rays from the publicly accessible dataset released as part of the 2018 RSNA Pneumonia Detection Challenge. We fine-tuned model hyperparameters using Bayesian optimization. Additionally, we assessed the robustness of SimplePNUnet across different downsampling techniques and batch sizes. Performance of the algorithm was evaluated using the area under receiver operating characteristic curve (AUROC). The performance of the best model across the training (n=1000), validation (n=500), and test (n=500) sets was comparable (AUC, 0.870 vs 0.812 vs 0.834, respectively) and within range of U-Net based pneumonia detection algorithms (AUC, 0.80-0.90). SimplePNUnet achieved good performance on an external validation set (AUC, 0.712).
Nancy F. Yuan is a PhD researcher in machine learning at UC San Diego in the Bioinformatics and Systems Biology program. She is currently working in finance. She has developed machine learning and deep learning approaches for predicting clinical outcomes for patients with respiratory diseases like COVID-19 and COPD. More broadly, she is passionate about developing technologies to improve predictive analytics across finance, health, and other data-driven industries. In her spare time, she enjoys reading and writing fiction and poetry, as well as snuggling with her two kitties, Max and Leo. She loves meandering walks on the beach, and taking pictures that she shares on Instagram (@fanci_nanci).