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QMS
  • Welcome to your QMS
  • Quality Manual
  • Procedures
    • GP-001 Control of documents
    • GP-002 Quality planning
    • GP-003 Audits
    • GP-004 Vigilance system
    • GP-005 Human Resources and Training
    • GP-006 Non-conformity, Corrective and Preventive actions
    • GP-007 Post-market surveillance
    • GP-008 Product requirements
    • GP-009 Sales
    • GP-010 Purchases and suppliers evaluation
    • GP-011 Provision of service
    • GP-012 Design, Redesign and Development
      • Deprecated
      • Templates
        • T-012-001 Requirements
        • T-012-003 Test run
        • T-012-004 Software version release
        • T-012-005 Design change control
        • T-012-006 _Product name_ life cycle plan and report_YYYY_nnn
        • T-012-007 Formative evaluation plan_YYYY_nnn
        • T-012-008 Formative evaluation report_YYYY_nnn
        • T-012-009 Validation and testing of machine learning models_YYYY_nnn
        • T-012-010 Device backup verification_YYYY_nnn
        • T-012-012 Customers product version control_YYYY_nnn
        • T-012-013 Design stage review
        • T-012-014 Summative evaluation plan_YYYY_nnn
        • T-012-015 Summative evaluation report YYYY_nnn
        • T-012-016 Software usability test guide
        • T-012-017 Integration test review
        • T-012-018 Test plan
        • T-012-019 SOUP
        • T-012-020 Predetermined Change Control Plan
      • Specific procedures
    • GP-013 Risk management
    • GP-014 Feedback and complaints
    • GP-015 Clinical evaluation
    • GP-016 Traceability and identification
    • GP-017 Technical assistance service
    • GP-018 Infrastructure and facilities
    • GP-019 Software validation plan
    • GP-020 QMS Data analysis
    • GP-021 Communications
    • GP-022 Document translation
    • GP-023 Change control management
    • GP-024 Cybersecurity
    • GP-025 Corporate Governance
    • GP-026 Product requirements for US market
    • GP-027 Product requirements for UK market
    • GP-028 Product requirements for the Brazilian market
    • GP-050 Data Protection
    • GP-051 Security violations
    • GP-052 Data Privacy Impact Assessment (DPIA)
    • GP-100 Business Continuity (BCP) and Disaster Recovery plans (DRP)
    • GP-101 Information security
    • GP-200 Remote Data Acquisition in Clinical Investigations
  • Records
  • TF_Legit.Health_Plus
  • Licenses and accreditations
  • External documentation
  • Procedures
  • GP-012 Design, Redesign and Development
  • Templates
  • T-012-009 Validation and testing of machine learning models_YYYY_nnn

T-012-009 Validation and testing of machine learning models_YYYY_nnn

Description of the methodologies​

info

The sections provided below are examples. Please add the sections you require and/or remove those you don't.

Common practices​

Image recognition​

Object detection​

Signature meaning

The signatures for the approval process of this document can be found in the verified commits at the repository for the QMS. As a reference, the team members who are expected to participate in this document and their roles in the approval process, as defined in Annex I Responsibility Matrix of the GP-001, are:

  • Author: Team members involved
  • Reviewer: JD-003, JD-004
  • Approver: JD-001
Delete this

Delete this section when you create a new record from this template.

Signature meaning

The signatures for the approval process of this document can be found in the verified commits at the repository for the QMS. As a reference, the team members who are expected to participate in this document and their roles in the approval process, as defined in Annex I Responsibility Matrix of the GP-001, are:

  • Author: Team members involved
  • Reviewer: JD-003, JD-004
  • Approver: JD-001
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T-012-008 Formative evaluation report_YYYY_nnn
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  • Description of the methodologies
    • Common practices
    • Image recognition
    • Object detection
All the information contained in this QMS is confidential. The recipient agrees not to transmit or reproduce the information, neither by himself nor by third parties, through whichever means, without obtaining the prior written permission of Legit.Health (AI LABS GROUP S.L.)