Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation

1 April 2023

Papers citing "Evaluating the impact of an explainable machine learning system on the interobserver agreement in chest radiograph interpretation"

7 / 7 papers shown

Title
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese Thao T. B. Nguyen T. M. Vo Thang V. Nguyen Hieu H. Pham H. Nguyen 69 4 0 11 Sep 2022
Learning from Multiple Expert Annotators for Enhancing Anomaly Detection in Medical Image Analysis Khiem H. Le Tuan V. Tran Hieu H. Pham Hieu T. Nguyen T. Le H. Nguyen 55 25 0 20 Mar 2022
Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks Thanh-Truong Tran H. Pham T. Nguyen T. Le H. T. Nguyen H. Q. Nguyen 43 11 0 14 Aug 2021
Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease Dependencies and Uncertainty Labels Hieu H. Pham T. Le Dat Ngo Dat Q. Tran H. Nguyen 76 164 0 25 May 2020
CheXclusion: Fairness gaps in deep chest X-ray classifiers Laleh Seyyed-Kalantari Guanxiong Liu Matthew B. A. McDermott Irene Y. Chen Marzyeh Ghassemi OOD 103 293 0 14 Feb 2020
EfficientDet: Scalable and Efficient Object Detection Mingxing Tan Ruoming Pang Quoc V. Le 120 5,076 0 20 Nov 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 172 18,193 0 28 May 2019