Table 1 Examples of data variabilities within the intended use20, 26, 36, 38,39,40, 61, 136,137,138.

From: Recommendations on compiling test datasets for evaluating artificial intelligence solutions in pathology

Origin

Variabilities

Patient

• Patient ethnicity

• Patient demographics

• Disease stage/severity

• Rare cases of disease

• Comorbidities

• Biological differences (genetic, transcriptional, epigenetic, proteomic, and metabolomic)

Specimen sampling

• Tissue heterogeneity

• Size of tissue section

• Coverage of diseased/healthy/boundary regions

• Tissue damage, e.g., torn, cauterized

• Surgical ink present

Slide processing

• Inter-material and device differences

• Preparation differences (fixation, dehydration; freezing; mechanical handling)

• Cutting artifacts (torn, folded, deformed, thick or inhomogeneously thick tissue)

• Foreign matter/floaters in specimen

• Over-/under-staining, inhomogeneous staining

• Foreign objects on slide/cover slip (dirt, stain residue, pen markings, fingerprint)

• Cracks, air bubbles, scratches

• Slide age

Imaging/image processing

• Inter- and intra-scanner differences

• Out-of-focus images, heterogeneous focus

• Amount of background in analyzed image region

• Magnification/image resolution

• Heterogeneous illumination

• Grid noise, stitching artifacts

• Lossy image compression

Ground truth annotation

• Inter- and intra-observer differences

• Ambiguous cases