R-TF-001-007 Declaration of conformity

This is a draft

This document is a draft version.

AI Labs Group SL, located at Gran Vía 1, BAT Tower, 48001, Bilbao, Bizkaia (Spain), with SRN ES-MF-000025345, certifies under its responsibility that the manufactured product:

	Information
Device name	Legit.Health Plus (hereinafter, the device)
Version	1.0.0.0
Basic UDI-DI	8437025550LegitCADx6X
Intended purpose	The complete intended purpose can be consulted below, in the section Intended use or purpose.
GMDN code	65975
EMDN code	Z12040192 (General medicine diagnosis and monitoring instruments - Medical device software)

Complies with the applicable standards:

UNE-EN ISO 13485:2018 (EN ISO 13485:2016) Medical devices - Quality management systems - Requirements for regulatory purposes
UNE-EN 62304:2007/A1:2016 (EN 62304:2006/A1:2015) Medical device software - Software life-cycle processes
UNE-EN ISO 14971:2020 (EN ISO 14971:2019) Medical devices - Application of risk management to medical devices
UNE-EN ISO 15223-1:2022 (EN ISO 15223-1:2021) Medical devices - Symbols to be used with information to be supplied by the manufacturer - Part 1: General requirements
UNE-EN ISO 20417:2021 (EN ISO 20417:2021) Medical devices - Information to be supplied by the manufacturer
UNE-EN 62366-1:2015/A1:2020 (EN 62366-1:2015/A1:2020) Medical devices - Part 1: Application of usability engineering to medical devices
UNE-EN ISO 14155:2021 (EN ISO 14155:2020) Clinical investigation of medical devices for human subjects - Good clinical practice

There are no common specifications applicable to the device.

Complies with the provisions of the Regulation (EU) 2017/745 of the European Parliament and of the Council on Medical Devices and issued under the exclusive responsibility of AI Labs Group SL.

Classification: Class IIa (Rule 11)

The conformity assessment route is based on a quality management system and on assessment of technical documentation according to the Annex IX (Chapters I and III) of the above mentioned regulation.

Certificate ID: MDR 792790

Notified body: BSI (British Standards Institution) number 2797.

All documentation supporting this CE Declaration of Conformity is preserved in the document management system of the manufacturer, supported by the Quality System approval to ISO 13485 by BSI.

This document was issued in Bilbao, on the following date:

Signature and date
General Manager full name

Intended use or purpose

Intended use

an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image
quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others

Quantification of intensity, count and extent of visible clinical signs

The device provides quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others; including, but not limited to:

erythema,
desquamation,
induration,
crusting,
xerosis (dryness),
swelling (oedema),
oozing,
excoriation,
lichenification,
exudation,
wound depth,
wound border,
undermining,
hair loss,
necrotic tissue,
granulation tissue,
epithelialization,
nodule,
papule
pustule,
cyst,
comedone,
abscess,
draining tunnel,
inflammatory lesion,
exposed wound, bone and/or adjacent tissues,
slough or biofilm,
maceration,
external material over the lesion,
hypopigmentation or depigmentation,
hyperpigmentation,
scar,
ictericia

Image-based recognition of visible ICD categories

The device is intended to provide an interpretative distribution representation of possible International Classification of Diseases (ICD) categories that might be represented in the pixels content of the image.

Device description

The device is a computational software-only medical device leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures. Its principal function is to provide a wide range of clinical data from the analyzed images to assist healthcare practitioners in their clinical evaluations and allow healthcare provider organisations to gather data and improve their workflows.

The generated data is intended to aid healthcare practitioners and organizations in their clinical decision-making process, thus enhancing the efficiency and accuracy of care delivery.

The device should never be used to confirm a clinical diagnosis. On the contrary, its result is one element of the overall clinical assessment. Indeed, the device is designed to be used when a healthcare practitioner chooses to obtain additional information to consider a decision.

Intended medical indication

The device is indicated for use on images of visible skin structure abnormalities to support the assessment of all diseases of the skin incorporating conditions affecting the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

Intended patient population

The device is intended for use on images of skin from patients presenting visible skin structure abnormalities, across all age groups, skin types, and demographics.

Intended user

The medical device is intended for use by healthcare providers to aid in the assessment of skin structures.

User qualifications and competencies

This section outlines the qualifications and competencies required for users of the device to ensure its safe and effective use. It is assumed that all users already possess the baseline qualifications and competencies associated with their respective professional roles.

Healthcare professionals

No additional official qualifications are required for healthcare professionals (HCPs) to use the device. However, it is recommended that HCPs possess the following competencies to optimize device utilization:

Proficiency in capturing high-quality clinical images using smartphones or equivalent digital devices.
Basic understanding of the clinical context in which the device is applied.
Familiarity with interpreting digital health data as part of the clinical decision-making process.

The device may be used by any healthcare professional who, by virtue of their academic degree, professional license, or recognized qualification, is authorized to provide healthcare services. This includes, but is not limited to:

Medical Doctors (MD, MBBS, DO, Dr. med., or equivalent)
Registered Nurses (RN, BScN, MScN, Dipl. Pflegefachfrau/-mann, or equivalent)
Nurse Practitioners (NP, Advanced Nurse Practitioner, or equivalent)
Physician Assistants (PA, or equivalent roles such as Physician Associate in the UK/EU)
Dermatologists (board-certified, Facharzt für Dermatologie, or equivalent)
Other licensed or registered healthcare professionals as recognized by local, national, or European regulatory authorities

Each HCP must hold the academic title, degree, or professional registration that confers their status as a healthcare professional in their jurisdiction, whether in the United States, Europe, or other regions where the device is provided.

IT professionals

IT professionals are responsible for the technical integration, configuration, and maintenance of the medical device within the healthcare organization's information systems.

No specific official qualifications are mandated. Nevertheless, it is advisable that IT professionals involved in the deployment and support of the device have the following competencies:

Foundational knowledge of the HL7 FHIR (Fast Healthcare Interoperability Resources) standard and its application in healthcare data exchange.
Ability to interpret and manage the device's data outputs, including integration with electronic health record (EHR) systems.
Understanding of healthcare data privacy and security requirements relevant to medical device integration, including GDPR (Europe), HIPAA (US), and other applicable local regulations.
Experience with troubleshooting and supporting clinical software in a healthcare environment.
Familiarity with IT standards and best practices for healthcare, such as ISO/IEC 27001 (Information Security Management) and ISO 27799 (Health Informatics—Information Security Management in Health).

IT professionals may include, but are not limited to:

Health Informatics Specialists (MSc Health Informatics, or equivalent)
Clinical IT System Administrators
Healthcare Integration Engineers
IT Managers and Project Managers in healthcare settings
Software Engineers and Developers specializing in healthcare IT
Other IT professionals with relevant experience in healthcare environments, as recognized by local, national, or European authorities

Each IT professional should possess the relevant academic degree, professional certification, or demonstrable experience that qualifies them for their role in the healthcare organization, in accordance with the requirements of the United States, Europe, or other regions where the device is provided.

Use environment

The device is intended to be used in the setting of healthcare organisations and their IT departments, which commonly are situated inside hospitals or other clinical facilities.

The device is intended to be integrated into the healthcare organisation's system by IT professionals.

Operating principle

The device is computational medical tool leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures.

Body structures

The device is intended to use on the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).

In fact, the device is intended to use on visible skin structures. As such, it can only quantify clinical signs that are visible, and distribute the probabilities across ICD categories that are visible.

Explainability

For visual signs that can be quantified in terms of count and extent, the underlying models not only calculate a final value, such as the number of lesions, but also determine their locations within the image. Consequently, the output for these visual signs is accompanied by additional data, which varies depending on whether the quantification involves count or extent.

Count. When a visual sign is quantifyed by counting, the device generates bounding boxes for each detected entity. These bounding boxes are defined by their x and y coordinates, as well as their height and width in pixels.
Extent. When a visual sign is quantifyed by its extent, the device outputs a mask. This mask, which is the same size as the image, consists of 0's for pixels where the visual sign is absent and 1's for pixels where it is present.

The explainability output can be found with the explainabilityMedia key. Here is an example:

{
  "explainabilityMedia": {
    "explainabilityMedia": {
      "content": "base 64 image",
      "detections": [
        {
          "confidence": 98,
          "label": "nodule",
          "p1": {
            "x": 202,
            "y": 101
          },
          "p2": {
            "x": 252,
            "y": 154
          }
        },
        {
          "confidence": 92,
          "label": "pustule",
          "p1": {
            "x": 130,
            "y": 194
          },
          "p2": {
            "x": 179,
            "y": 245
          }
        }
      ]
    }
  }
}

Record signature meaning

Author: JD-004 María Diez
Review: JD-005 Alfonso Medela
Approval: JD-001 Andy Aguilar

Intended use or purpose​