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. 2022 Sep 28;10(10):1892. doi: 10.3390/healthcare10101892

Table 12.

Performance measures of deep learning methods.

Study Accuracy Precision Recall F1 score Sensitivity Specificity FP AUC ROC PRC mIOU FPR NPV FNR mAP IOU FDR MCC dice DSC DA FA Jaccard
De Araujo Faria et al., (2021) [41]
Li et al., (2021) [42]
Geetha et al., (2020) [43]
Zanella-Calzada et al., (2018) [44]
Li et al., (2018) [47]
Lu et al., (2018) [48]
Li et al., (2018) [49]
Alarifi and AlZubi, (2018) [51]
Kumari et al., (2022) [52]
Singh and Sehgal, (2021) [53]
Prajapati et al., (2017) [16]
Lee et al., (2018) [56]
Vinayahalingam et al., (2021) [57]
Choi et al., (2018) [63]
Lee et al., (2021) [65]
Yang et al., (2018) [67]
Lee et al., (2018) [68]
Al Kheraif et al., (2019) [69]
Murata et al., (2019) [70]
Krois et al., (2019) [72]
Zhao et al., (2020) [77]
Fariza et al., (2020) [78]
Lakshmi and Chitra, (2020) [79]
Khan et al., (2021) [80]
Moran et al., (2020) [81]
Chen et al., (2021) [82]
Lin and Chang, (2021) [84]
Zhang et al., (2022) [85]
Yu et al., (2020) [91]
Rana et al., (2017) [92]
Tanriver et al., (2021) [94]
Schlickenrieder et al., (2021) [95]
Takahashi et al., (2021) [96]
Zhang et al., (2021) [102]
Zheng et al., (2022) [103]
Adel et al., (2018) [111]
Chatterjee et al., (2018) [112]
Xu et al., (2018) [114]
Tian et al., (2019) [115]
Cui et al., (2021) [120]
Kang et al., (2022) [121]
Chen, (2021) [122]
Miki et al., (2017) [124]
Sorkhabi and Khajeh, (2019) [125]
Jaskari et al., (2020) [126]
Kwak et al., (2020) [127]
Kim et al., (2020) [129]
Orhan et al., (2020) [130]
Cui et al., (2019) [131]
Chen et al., (2020) [132]
Lee et al., (2020) [133]
Wang et al., (2021) [134]
Hiraiwa et al., (2019) [135]
Lee et al., (2020) [136]
Ezhov et al., (2021) [137]
Qiu et al., (2021) [138]