The higher rate of adherence in patients aged 65 and older to the referral for a chest x-ray can be explained by acknowledgement of the threat of pneumonia at older age. In the absence of radiology evidence for pneumonia, the medical decision is empirical and based on evidence with weak ...
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The proposed model is trained on ChestX-Ray14, which is a publicly accessible chest X-ray dataset. The best single model achieves an overall precision, recall, F-1 measure and area under curve (AUC) scores of 0.87, 0.85, 0.86 and 0.89, respectively, for the classification of the ...
Standardized, automated labeling method, based on similarity to a previously validated five-label chest X-ray (CXR) detection explainable AI (xAI) model, using an xAI model-derived-atlas based approach. a Our quantitative model-derived atlas-based explainable AI system calculates a probability-of-...
chest X-rays. We trained and tested the AI system on a large dataset, assessed generalizability on publicly available data, and evaluated radiologist and non-radiologist physician accuracy when unaided and aided by the AI system. The AI system accurately detected chest X-ray abnormalities (AUC: ...
Superiority of lung US findings over CXR findings could be explained by high sensitivity & specificity of lung US in diagnosing pneumonia in comparison with chest x ray as high resolution CT is a gold standred for the study.LUS is a sensitive and highly specific diagnostic tool in pneumonia. ...
Introduction: Chest X-ray (CXR) is used for the initial triage of patients with suspected COVID-19. Studies of CXR scoring in the European population found a higher score in males than in females and significantly correlated with age. Because there have not been studies in the Mexican-mestizo...
Preprocessing is an essential task for the correct analysis of digital medical images. In particular, X-ray imaging might contain artifacts, low contrast, diffractions or intensity inhomogeneities. Recently, we have developed a procedure named PACE that
The introduction of x-ray technology in the early part of the last century gave medical workers a chance to see a silhouette of the structures inside the human for the first time. The result of this advance was revolutionary. A physician’s ability to detect disease expanded beyond what could...
As explained before, the ensemble consists of five models. We generate ensemble heatmaps by averaging the individual heatmaps generated by those models. Finally, we generate a of the average heatmap of each classifier neuron, which is overlaid on the original X-ray using a 10% of transparen...