# Image Classification on Medical Imaging Dataset Source: [Image Classification on Medical Imaging Dataset]() Collection index: [llms.txt]() Data updated: 2026-02-26T05:31:31.838Z Evaluation of Image Classification performance on the Medical Imaging Dataset, utilizing standard metrics including Accuracy, AUC, F1 score, Sensitivity, and Specificity. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Image Classification | | Dataset (including any stated split) | Medical Imaging Dataset | | Metric | Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 5 of 5 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Accuracy](): Higher is better; unit: PERCENT. - [AUC](): Higher is better; unit: PERCENT. - [F1 Score](): Higher is better; unit: PERCENT. - [Precision](): Higher is better; unit: PERCENT. - [Recall](): Higher is better; unit: PERCENT. - [Sensitivity](): Higher is better; unit: PERCENT. - [Specificity](): Higher is better; unit: PERCENT. ## Recorded results | Method | Accuracy | Result date | Report paper | | --- | --- | --- | --- | | DG-Quantum | 96.67 | Not recorded | 697846fca2b28e761d87c88d | | ResNet18 | 93.33 | Not recorded | 697846fca2b28e761d87c88d | | MobileNetV2 | 87.5 | Not recorded | 697846fca2b28e761d87c88d | | EfficientNet-B0 | 87.5 | Not recorded | 697846fca2b28e761d87c88d | | SimpleCNN | 56.67 | Not recorded | 697846fca2b28e761d87c88d | ### DG-Quantum Accuracy: 96.67. Result ID: 699790225698665ec4e573df. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"parameter count":"3.5M"}. This record does not assert independent reproduction. ### ResNet18 Accuracy: 93.33. Result ID: 699790225698665ec4e573e0. [Reporting paper]() Recorded evaluation configuration: {"parameter count":"11M"}. This record does not assert independent reproduction. ### MobileNetV2 Accuracy: 87.5. Result ID: 699790225698665ec4e573e1. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### EfficientNet-B0 Accuracy: 87.5. Result ID: 699790225698665ec4e573e2. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. ### SimpleCNN Accuracy: 56.67. Result ID: 699790225698665ec4e573e3. [Reporting paper]() Recorded evaluation configuration: Not recorded. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.