Dynamic Prediction of SARS-CoV-2 RT-PCR status on Chest Radiographs using Deep Learning Enabled Radiogenomics
Chiu, W. H. K.; Poplavskiy, D.; Zhang, S.; Yu, P. L. H.; Kuo, M. D.
Show abstract
Reverse Transcription-Polymerase Chain Reaction (RT-PCR) is the gold standard for diagnosis of SARS-CoV-2 infection, but requires specialized equipment and reagents and suffers from long turnaround times. While valuable, chest imaging currently only detects COVID-19 pneumonia, but if it can predict actual RT-PCR SARS-CoV-2 status is unknown. Radiogenomics may provide an effective and accurate RT-PCR-based surrogate. We describe a deep learning radiogenomics (DLR) model (RadGen) that predicts a patient's RT-PCR SARS-CoV-2 status solely from their frontal chest radiograph (CXR).
Matching journals
The top 7 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Radiosafe micro-computed tomography for longitudinal evaluation of murine disease models 92%
- High-Dimensional Multinomial Multiclass Severity Scoring of COVID-19 Pneumonia Using CT Radiomics Features and Machine Learning Algorithms 91%
- Identifying relationships between imaging phenotypes and lung cancer-related mutation status: EGFR and KRAS 91%
Similar papers in this journal
- Integration of machine learning and genome-scale metabolic modeling identifies multi-omics biomarkers for radiation resistance 92%
- Integration of clinical characteristics, lab tests and a deep learning CT scan analysis to predict severity of hospitalized COVID-19 patients 92%
- Priming versus propagating: distinct immune effects of an alpha- versus beta-particle emitting radiopharmaceutical when combined with immune checkpoint inhibition 91%
Similar papers in this journal
- Tumor-localized interleukin-2 and interleukin-12 combine with radiation therapy to safely potentiate regression of advanced malignant melanoma in pet dogs 89%
- PARP1/2 imaging with 18F-PARPi in patients with head and neck cancer 88%
- Human Papilloma Virus Circulating Cell-Free DNA Kinetics in Cervical Cancer Patients Undergoing Definitive Chemoradiation 88%
Similar papers in this journal
- From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans 89%
- A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19) 89%
- Predicting EGFR mutation status in lung adenocarcinoma presenting as ground-glass opacity: utilizing radiomics model in clinical translation 87%
Similar papers in this journal
- X-ray Dark-Field Chest Imaging can Detect and Quantify Emphy-sema in COPD Patients 89%
- Novel deep learning algorithm predicts the status of molecular pathways and key mutations in colorectal cancer from routine histology images 89%
- Development and validation of AI-based pre-screening of large bowel biopsies 88%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.