Journal: Multimedia Systems

Article Title: A survey on the interpretability of deep learning in medical diagnosis

doi: 10.1007/s00530-022-00960-4

Figure Lengend Snippet: The experimental results of diagnosing various eye diseases (such as diabetic retinopathy, glaucoma, etc.) on different datasets

Article Snippet: Detect referable diabetic retinopathy(RDR) , Chetoui et al. [ ] , EfficientNet , EyePACS , Grad-CAM , 91.70% , 98.90% , – , 0.984.

Techniques: Biomarker Discovery, Activation Assay

Journal: Journal of Visualization

Article Title: Ultrasonic tomography imaging enhancement approach based on deep convolutional neural networks

doi: 10.1007/s12650-023-00922-6

Figure Lengend Snippet: EfficientNet encoder part’s blocks structure

Article Snippet: The application of transfer learning for segmentation purposes has extended beyond medical images and has been utilized for inspecting materials and detecting flaws in ultrasonic images (Medak et al. ), applying EfficientNet as an encoder of U-Net (Wu et al. ).

Techniques:

Journal: Chaos, Solitons, and Fractals

Article Title: C+EffxNet: A novel hybrid approach for COVID-19 diagnosis on CT images based on CBAM and EfficientNet

doi: 10.1016/j.chaos.2021.111310

Figure Lengend Snippet: EfficientNet B0 structure.

Article Snippet: Again, Chowdhury and his colleagues tried to identify COVID-19 on X-ray images in the approach they developed using the EfficientNet model.

Techniques:

Journal: Chaos, Solitons, and Fractals

Article Title: C+EffxNet: A novel hybrid approach for COVID-19 diagnosis on CT images based on CBAM and EfficientNet

doi: 10.1016/j.chaos.2021.111310

Figure Lengend Snippet: COVID-19/normal classification results. DL: Deep Learning Ref.: reference.

Article Snippet: Again, Chowdhury and his colleagues tried to identify COVID-19 on X-ray images in the approach they developed using the EfficientNet model.

Techniques:

Journal: Scientific Reports

Article Title: CytoNet: an efficient dual attention based automatic prediction of cancer sub types in cytology studies

doi: 10.1038/s41598-024-76512-9

Figure Lengend Snippet: Summary of related work.

Article Snippet: Tomko , Training standard DNNs and EfficientNet-B0 model , Investigated cervical cancer classification using datasets from Intel and MobileODT Cervical Cancer Screening competition, exploring training standard DNNs and EfficientNet-B0 model..

Techniques: Extraction, Biomarker Discovery, Diagnostic Assay, Selection