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Resumen de: US12694957B1

0000 A system for generation of diagnosis parameters based on patient-related data, including a processor of a classification server node configured to host a machine learning module and connected to an interview entity node and to at least one medical entity node over a network; and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire sensory data from a plurality of biosensors encapsulated into a patient wearable device; receive patient interview data from the interview entity node comprising audio data generated during patient interview; derive a language metadata from the interview data; parse the interview data based on the language metadata to derive a plurality of key features; query a local patients' database to retrieve local historical patients'-related data related to previous patients' engagements associated with previous interview data based on the plurality of features; generate at least one feature vector based on the plurality of features, the sensory data and the local historical patients'-related data; and provide the at least one feature vector to the ML module configured to generate a predictive model for producing at least one diagnosis parameter for generation of the patient-related classification for the at least one medical entity node.