Endpoint Parameters

Severity Experts

This endpoint returns the full list of available severity experts that can be used when calling the severity-assessment endpoint. Each expert corresponds to a specific AI model capable of detecting or classifying a particular clinical sign or feature in a skin image.

Endpoint URL:

https://plus.legit.health/v1.0/clinical/severity-experts

Authentication

This endpoint requires an Authorization header with a valid bearer token. The token can be obtained from the login endpoint:

https://plus.legit.health/v1.0/auth/login

Example Response

{
  "experts": [
    "abscess_detector",
    "acneiform_detector",
    "awosi_classifier",
    "body_surface_segmenter",
    "crusting_classifier",
    "desquamation_classifier",
    "draining_tunnel_detector",
    "dryness_classifier",
    "erythema_classifier",
    "erythema_segmenter",
    "excoriation_classifier",
    "follicular_inflammatory_pattern_classifier",
    "hair_follicle_detector",
    "hair_loss_segmenter",
    "head_detector",
    "hive_detector",
    "hyperpigmentation_segmenter",
    "hypopigmentation_segmenter",
    "induration_classifier",
    "inflammatory_nodular_lesion_detector",
    "inflammatory_pattern_identificator",
    "lichenification_classifier",
    "nail_lesion_segmenter",
    "nodule_detector",
    "oedema_classifier",
    "oozing_classifier",
    "pimple_detector",
    "pustule_classifier",
    "skin_segmenter",
    "swelling_classifier",
    "tissue_wound_bed_closed_classifier",
    "tissue_wound_bed_necrotic_classifier",
    "wound_affected_tissues_bone_classifier",
    "wound_affected_tissues_dermis_epidermis_classifier",
    "wound_affected_tissues_intact_classifier",
    "wound_affected_tissues_muscle_classifier",
    "wound_affected_tissues_subcutaneous_classifier",
    "wound_bed_segmenter",
    "wound_biofilm_segmenter",
    "wound_biofilm_tissue_classifier",
    "wound_bone_segmenter",
    "wound_borders_damaged_classifier",
    "wound_borders_delimited_classifier",
    "wound_borders_diffused_classifier",
    "wound_borders_indistinguishable_classifier",
    "wound_borders_thickened_classifier",
    "wound_depth_classifier",
    "wound_epithelialization_segmenter",
    "wound_exposure_segmenter",
    "wound_external_contamination_segmenter",
    "wound_exudation_classifier",
    "wound_granulation_segmenter",
    "wound_maceration_segmenter",
    "wound_necrosis_segmenter",
    "wound_orthopedic_segmenter",
    "wound_perilesional_erythema_classifier",
    "wound_perilesional_maceration_classifier",
    "wound_slough_segmenter",
    "wound_stage_classifier",
    "wound_tissue_wound_bed_epithelial_classifier",
    "wound_tissue_wound_bed_granulation_classifier",
    "wound_tissue_wound_bed_slough_classifier",
    "wound_type_exudation_bloody_classifier",
    "wound_type_exudation_fibrinous_classifier",
    "wound_type_exudation_purulent_classifier",
    "wound_type_exudation_serous_classifier",
    "wound_undermining_classifier",
    "xerosis_classifier"
  ]
}

Usage with the Severity Assessment Endpoint

The list of experts returned by this endpoint is used to populate the experts array in the request body of the severity-assessment endpoint:

https://plus.legit.health/v1.0/clinical/severity-assessment

Select the experts relevant to your use case and include them in the request body alongside the image data:

Example request body for severity-assessment

{
  "image": {
    "data": "base64",
    "colorModel": "rgb",
    "fileFormat": "jpeg"
  },
  "experts": [
    "erythema_classifier",
    "desquamation_classifier",
    "induration_classifier",
    "erythema_segmenter"
  ]
}

Tip

You do not need to send all available experts in every request. Choose only the experts that are relevant to the clinical signs you wish to assess.