Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386232022> ?p ?o ?g. }
Showing items 1 to 73 of
73
with 100 items per page.
- W4386232022 abstract "Pulmonary fibrosis (PF) is a chronic lung disease characterized by the formation of scar tissue in the lungs, leading to difficulty breathing and a reduced ability to oxygenate the blood. The progression of PF is difficult to predict, and current methods of diagnosis and treatment are often ineffective. In this study, we propose to use EfficientNet, utilizing a cutting-edge convolutional neural network (CNN) architecture and quantile regression (QR) to predict the progression of PF in patients. Our approach includes analyzing data from the OSIC dataset, the biggest publicly accessible dataset containing medical imaging, patient demographics, and lab results. The analyzed data was trained on an EfficientNet model and QR to predict the progression of the disease, as well as estimate the uncertainty of the predictions. The performance of the model was evaluated using Laplace-Log-Likelihood. The results demonstrate that the proposed approach outperforms existing literature in predicting pulmonary fibrosis progression, with the highest score (-6.64). This approach has the potential to aid in the development of new treatments for this disease." @default.
- W4386232022 created "2023-08-29" @default.
- W4386232022 creator A5038359939 @default.
- W4386232022 creator A5039033335 @default.
- W4386232022 creator A5092812304 @default.
- W4386232022 creator A5092812305 @default.
- W4386232022 date "2023-09-06" @default.
- W4386232022 modified "2023-09-27" @default.
- W4386232022 title "Accurate Prediction of Pulmonary Fibrosis Progression Using EfficientNet and Quantile Regression: A High Performing Approach" @default.
- W4386232022 cites W1806301233 @default.
- W4386232022 cites W2174486202 @default.
- W4386232022 cites W2599075603 @default.
- W4386232022 cites W2889197569 @default.
- W4386232022 cites W3095755528 @default.
- W4386232022 cites W3209789324 @default.
- W4386232022 cites W3211084592 @default.
- W4386232022 doi "https://doi.org/10.1109/tensymp55890.2023.10223673" @default.
- W4386232022 hasPublicationYear "2023" @default.
- W4386232022 type Work @default.
- W4386232022 citedByCount "0" @default.
- W4386232022 crossrefType "proceedings-article" @default.
- W4386232022 hasAuthorship W4386232022A5038359939 @default.
- W4386232022 hasAuthorship W4386232022A5039033335 @default.
- W4386232022 hasAuthorship W4386232022A5092812304 @default.
- W4386232022 hasAuthorship W4386232022A5092812305 @default.
- W4386232022 hasConcept C105795698 @default.
- W4386232022 hasConcept C118671147 @default.
- W4386232022 hasConcept C119857082 @default.
- W4386232022 hasConcept C126322002 @default.
- W4386232022 hasConcept C152565575 @default.
- W4386232022 hasConcept C154945302 @default.
- W4386232022 hasConcept C202444582 @default.
- W4386232022 hasConcept C2780559512 @default.
- W4386232022 hasConcept C2781244666 @default.
- W4386232022 hasConcept C33923547 @default.
- W4386232022 hasConcept C41008148 @default.
- W4386232022 hasConcept C63817138 @default.
- W4386232022 hasConcept C71924100 @default.
- W4386232022 hasConcept C81363708 @default.
- W4386232022 hasConcept C83546350 @default.
- W4386232022 hasConcept C9652623 @default.
- W4386232022 hasConceptScore W4386232022C105795698 @default.
- W4386232022 hasConceptScore W4386232022C118671147 @default.
- W4386232022 hasConceptScore W4386232022C119857082 @default.
- W4386232022 hasConceptScore W4386232022C126322002 @default.
- W4386232022 hasConceptScore W4386232022C152565575 @default.
- W4386232022 hasConceptScore W4386232022C154945302 @default.
- W4386232022 hasConceptScore W4386232022C202444582 @default.
- W4386232022 hasConceptScore W4386232022C2780559512 @default.
- W4386232022 hasConceptScore W4386232022C2781244666 @default.
- W4386232022 hasConceptScore W4386232022C33923547 @default.
- W4386232022 hasConceptScore W4386232022C41008148 @default.
- W4386232022 hasConceptScore W4386232022C63817138 @default.
- W4386232022 hasConceptScore W4386232022C71924100 @default.
- W4386232022 hasConceptScore W4386232022C81363708 @default.
- W4386232022 hasConceptScore W4386232022C83546350 @default.
- W4386232022 hasConceptScore W4386232022C9652623 @default.
- W4386232022 hasLocation W43862320221 @default.
- W4386232022 hasOpenAccess W4386232022 @default.
- W4386232022 hasPrimaryLocation W43862320221 @default.
- W4386232022 hasRelatedWork W1571591180 @default.
- W4386232022 hasRelatedWork W1803059841 @default.
- W4386232022 hasRelatedWork W2381123498 @default.
- W4386232022 hasRelatedWork W2392998192 @default.
- W4386232022 hasRelatedWork W2781143519 @default.
- W4386232022 hasRelatedWork W2950658249 @default.
- W4386232022 hasRelatedWork W3043780870 @default.
- W4386232022 hasRelatedWork W3124352863 @default.
- W4386232022 hasRelatedWork W3125536927 @default.
- W4386232022 hasRelatedWork W4367694312 @default.
- W4386232022 isParatext "false" @default.
- W4386232022 isRetracted "false" @default.
- W4386232022 workType "article" @default.