Multimodal cognitive communications and collaborative knowledge exchange with visual neural networking and packetized augmented intelligence

Abstract

The invention enables multimodal cognitive communications, collaboration, consultation and instruction with multichannel multiplexed streaming imagery data. It also enables synchronous multiparty curation, multisensory annotation and metadata tagging, as well as multi-formatted encapsulation, saving and sharing of collaborated imagery data as packetized augmented intelligence. The invention acquires both live stream and archived medical modality imagery from network-connected medical devices, cameras, signals and sensors, as well as multi-omic [phenotypic, genomic, metabolomic and radiomic] clinical data from biometric maps and movies, hapmaps, heat maps and data stream visualizations. The invention also acquires both medical and non-medical streaming imagery data from image data repositories, documents and structured reports, workstations and mobile devices, as well as from wearable computing, signals and sensors. The invention enables networked teams to interactively communicate, concurrently collaborate and bi-directionally exchange multichannel multiplexed imagery data streams, singly or together, in real time or asynchronously, generally by curating, annotating and tagging imagery information objects. The invention encapsulates and saves collaborated imagery data, together with multisensory annotations and metadata tags, in standard file formats as packetized augmented intelligence. The invention enables recursive cognitive enrichment with augmented cognitive vismemes, and saves packetized imagery information objects, multisensory annotations and metadata tags in native file formats [PDF, MPEG, JPEG, XML, XMPP, OR, SVG and DAE[ as well as in formats compliant with standards for digital communications in medicine [DICOM]. The invention enables live stream multicasting of multimodal cognitive communications and collaborative knowledge exchange with multisensory [visual, auditory, haptic] annotation and tagging of streaming imagery data, as well as secure, encrypted transmission of packetized augmented intelligence across file sharing data networks for rapid, adaptive learning, specialist skills acquisition and interoperable health information exchange.