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1. Technical Specification 2. Conformance Testing 3. Performance Assessment

1. Technical Specifications

This page gives the links to the specification of Data Types specified by Technical Specification: AI for Health (MPAI-AIH) – Health Secure Platform (AIH-HSP) V1.o.

Acronym AIH Name JSON Acronym AIH Name JSON
AIH-AAP AAC Parameters X AIH-CRS Confirmation Response X
AIH-AAT AAC Token X AIH-DID DIA Data X
AIH-AHD AIH Data X AIH-DRQ DIA Request X
AIH-DAR AIH Data Access Request X AIH-ECQ ECG Object X
AIH-DML AIH Data MLicence X AIH-EEQ EEG Object X
AIH-DSR AIH Data Store Request X AIH-EHQ EHR Object X
AIH-MRQ AIM Request X AIH-GNO Genomics Object X
AIH-ARD ARA Data X AIH-HLD Health Data X
AIH-ATD Audit Data X AIH-LRQ Licence Request X
AIH-ARQ Audit Request X AIH-LSD Licensing Data X
AIH-ARS Audit Response X AIH-MIO Medical Image Object X
AIH-BMD Biometric Data X AIH-MRQ NN Model Request X
AIH-CRQ Confirmation Request X AIH-PRQ Processing Request X

2     Conformance testing

A Data instance of a Data Type specified by MPAI-MMC V2.3 Conforms with it if the JSON Data validate against the relevant MPAI-MMC V2.3 JSON Schema and if the Data Conforms with the relevant Data Qualifier, if present. MPAI-MMC V2.3 does not provide method for testing the Conformance of the Semantics of the Data instance to the MPAI-MMC V2.3 specification.

Conformance testing can be performed by a human using a JSON Validator to verify the Conformance of the syntax of JSON Data to the relevant JSON Schema; and, if the Data has a Qualifier, to verify that the syntax of the Data conforms with the relevant values in the Data Qualifier. Alternatively, Conformance testing can be performed by software implementing the steps above.

3     Performance Assessment

Performance is a multidimensional entity because it can have various connotations, and the Performance Assessment Specification should provide methods to measure how well an AIW performs its function, using a metric that depends on the nature of the function, such as:

  1. Quality: Performance Assessment measures the quality of the Data instance using a metric that depends on the nature of the Data, e.g., the word error rate (WER) of a string of characters representing a sentence compared to an idea sentence.
  2. Bias: Performance Assessment uses a metric that depends on the bias in the Data compared with reference Data related to certain attributes of the Data.  For instance, the Data may contain information about a particular geographic area when the ideal data do not .
  3. Legal compliance: Performance Assessment uses an appropriate metric to measure how well the Data instance complies with with a certain legal standard.

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