A recognition method of COVID-19 CT image based on ResNet network
Why this work is in the frame
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Bibliographic record
Abstract
In order to improve the diagnosis rate of COVID-19 patients, according to the analysis for CT image characteristics, a method based on ResNet for CT images to identify COVID-19 patients was proposed. Combining the ResNet50 network model, by adding channel attention mechanism, adding Dropout function, and embedding the Adam optimizer of cosine annealing method, the average recognition accuracy in this method can reach to 95% for the analysis of confusion matrix results, with high accuracy and low recall rate. The results show that ResNet50 network model with Grad-CAM function has high recognition accuracy for the COVID-19 CT images. Therefore, the automatic recognition method for COVID-19 CT images has a practical application value.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it