Skip to main content

Table 3 Model parameter estimates with the entire student sample

From: Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review

  

Used by

Availability of dataset

Public data (n = 22)

[25,26,27,28], [30,31,32], [34,35,36,37,38,39,40], [42, 44], [51,52,53,54,55,56]

Private data (n = 6)

[24, 29, 33, 41, 46, 49]

Public and private data (n = 6)

[43, 45, 47, 48, 50, 57]

Dimensionality of data

2D models (2D data) (n = 23)

[24], [26,27,28], [30,31,32], [34,35,36,37], [40, 41], [47,48,49,50], [52,53,54,55,56,57]

3D models (volumetric data) (n = 11)

[25, 29, 33, 38, 39], [42,43,44,45,46], [51]

Modality of image data

CT (n = 21)

[29, 30, 32, 33, 33, 34], [36,37,38,39,40,41,42], [44,45,46,47,48,49,50,51,52]

Histopathology (n = 11)

(n = 11) [24,25,26,27,28], [35], [53,54,55,56,57]

PET (n = 1)

[43]

CT and MRI (n = 1)

[39]