## 2 Related Work
### Segmentation
\begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Reference** & **Application/** & **Approach** & **Data** & **Metric** & **TL* \\  & **Task** & & & & \\ \hline [PERSON] et al., 2017[26] & Colomoscopy frame & Pre-trained AlexNet model & 4000 colonoscopy frames selected from 6 complete colonoscopy & AUC, diversity, entropy & ✓ \\  & **classification**, polypy & with active incremental & videos, 38 short colonoscopy videos from 38 different patients, & \\  & **detection**, pulmonary & fine-tuning method & 121 CT pulmonary angiography datasets with a total number of & \\  & embolism **detection** & & & 326 pulmonary embolisms & \\ \hline [PERSON] et al., 2016[27] & Colomoscopy frame & Pre-trained AlexNet model & 4000 colonoscopy frames selected from 6 complete colonoscopy & AUC, free-response & ✓ \\  & **classification**, polypy & with layer-wise fine-tuning & videos, 40 short colonoscopy videos from 38 different patients, & operating characteristic, \\  & **detection**, pulmonary & method & 121 CT pulmonary angiography datasets with a total number of & ROC curve, segmentation & \\  & embolism **detection**, & & 326 pulmonary embolism, 92 carotid intima-media thickness & \\  & **segmentation** & & & \\ \hline [PERSON] et al., 2018[28] & Age-related macular & Inception V3 model & 207,130 OCT images, 523 chest X-ray images from children, & Acc, cross-entropy loss, & ✓ \\  & degeneration and diabetic & pretrained on the ImageNet & including 3883 characterized as depicting pneumonia & sensitivity, specificity, \\  & macular edema & dataset & (2538 bacterial and 1345 viral) and 139 normal from a total of & weighted error ROC curve \\  & **detection** & & & \\ \hline [PERSON] et al., 2021[31] & Pancreatic cancer & Anatomy-aware transformer & pancreatic ductal adenocarcinoma CT scans dataset of 1627 patients & AUC, sensitivity, specificity & ✗ \\  & **classification** & with localization w-net & & & \\ \hline [PERSON] and B and Rivaz H 2021[202] & Breast cancer **classification** & ViT, pretrained V6C16, & BUS4 dataset which has 780 breast US images (133 normal images, & Acc, AUC & ✓ \\  & & ResNet+100 ergioV3, and & 437 malignant masses, and 220 benign tumors), Dataset B which & \\  & & NASNetLarge models based & has 163 images (110 benign masses and 53 cancerous masses) & \\  & & on the breast US dataset & & \\ \hline [PERSON] et al., 2021[30] & Breast cancer **classification** & DenseNet201 and & QIN-breast dataset from TCIA & Acc, precision, recall, & ✓ \\  & & ResNet152V2 & & f1-score & \\ \hline [PERSON] et al., 2021[33] & Fundus disease **classification** & Transformer, CNN & OIA dataset & Acc & ✗ \\  & **2022[34]** & Prostate cancer **classification** & ViT & Kaggle PANDA challenge dataset which has 10,616 images & F1-score, precision, recall & ✓ \\ \hline [PERSON] et al., 2017[29] & **Classification** of malignant & Deep CNNs with stochastic & 1655 digitized-screen film mammography views and 310 digital & AUC, ROC curves & ✓ \\  & and benign breast masses & gradient descent & mammography views with 2454 masses (1057 malignant, & \\  & & & 1397 benign) & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._