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. 2022 Nov 14;2022:2456550. doi: 10.1155/2022/2456550

Table 1.

Overview of papers using deep learning techniques for early stroke diagnosis.

References Study objective Date published DL-based approaches Optimal results Clinical implications Limitation
Shinohara et al. [69] Recognize acute cerebral ischemia (ACI) 2017 ANN Precision-0.92; sensitivity-0.80; specificity-0.86 Recognition of ACI and differentiation of ACI from stroke mimics at the initial examination Not separate patients with posterior circulation from anterior circulation stroke; not calculate precision based on stroke type or possible stroke pathogenesis; lack generalizability
Litjens et al. [67] Identify MCA 2017 3DCNN AUC-0.996; precision-recall AUC-0.563 Not yet at a level for routine clinical use Small sample data sizes and lack of external validation
Lisowska et al. [68] Identify HMCAS 2020 DCNN Sensitivity-0.82, specifcity-0.81, and AUC-0.869 For reference and improve the accuracy of detecting HMCAS No thin-slice CT
Cui et al. [70] AIS diagnosis via DWI and ADC images 2021 DeepSym-3D-CNN AUC-0.850 Early acute stroke diagnosis Small sample data sizes