Table 8 Domain generalization performance: evaluation of architectures (discovered on source datasets) on unseen external target datasets without retraining

From: Large language models driven neural architecture search for universal and lightweight disease diagnosis on histopathology slide images

Source dataset

Target external dataset

Backbone

Method

Performance (%)↑

BreakHis

SkinTumor27

ShuffleNet

Random Search

39.21 ± 0.57 (Prec@1)

BreakHis

SkinTumor27

ShuffleNet

Pathology-NAS

74.50 ± 0.98 (Prec@1)

BreakHis

SkinTumor27

ViT

Random Search

73.52 ± 0.94 (Prec@1)

BreakHis

SkinTumor27

ViT

Pathology-NAS

82.35 ± 0.29 (Prec@1)

BreakHis

SkinTumor27

MobileNetV3

Random Search

45.30 ± 0.70 (Prec@1)

BreakHis

SkinTumor27

MobileNetV3

Pathology-NAS

78.10 ± 0.60 (Prec@1)

PanNuke

Polyp28

U-Net

Random Search

39.18 ± 0.27 (Dice)

PanNuke

Polyp28

U-Net

Pathology-NAS

62.07 ± 0.45 (Dice)

  1. Performance metrics are reported as mean ± std. dev.