Re-imagine big data to imagine a better future, DIGITALLY TRANSFORMED.

Cubismi’s Decision Flow™-3D foundational Multimodal AI cloud technology will provide revolutionary predictive and prescriptive analytics within a revolutionary 3D experience for augmented medical decision-making that’s highly accurate, contextualized, and fast.

Foundational AI-cloud capabilities allow for multiple powerful new ways for software to augment physician decision-making and continually improve patient care pathways in a precision era.

‍The innovative system design leverages a cutting-edge Data Mesh / Data Fabric informatics technology to anatomically structure data from a potentially unlimited array of data sources, including medical imaging, genomics and proteomics, into holistic AI-enabled 3D-anatomical-time interactive virtual maps for each patient.

Combined with machine learning and AI algorithms, the system is designed for a leap for forward in ergonomic human-information interaction. Machine learning predictions from this structured data design allows for three major leaps forward. First, it will allow a new intuitive order by streamlining information flows to allow physicians to triage “signal from noise” during decision-making. Second, multi-modal data integrations will provide critically-needed granular "street view" biomarkers for cancer and other diseases. Last, this ground-breaking design will, for the first time, allow holistic integration of patient care outcomes metrics for "best routes" using Decision Intelligence (DI). This “connected intelligence” takes today's clinical prescriptive analytics to a new level. Applied across multiple physician and other decision-makers, the platform is designed to enable continuous improvement of patient care precision era pathways.

STREAMLINED Information FLOWS

Streamlined information flows will allow a new intuitive order designed for physicians' cognitive processing that is missing today. 3D data structuring using validated Data Mesh & Data Fabric technology allows virtual displays of high level metadata for expert information triage. For example, in the future and given enough data for training, the technology could allow displays of normal versus abnormal voxels in medical images.
This metadata display would allow experts to easily identify "signal from noise" and avoid sorting through millions of normal voxels during decision-making, as is done today.

Novel BIOMARKER information

Valuable precision insights from proprietary MULTIMODAL AI technology.

READ ABOUT MULTIMODAL AI IN LEADING SCIENCE JOURNALS

Multimodal AI for medicine, simplified, Eric Topol, MD, Ground Truths, March 2023 Multimodal Biomedical AI, Nature Medicine, Sept 2022 As artificial intelligence goes multimodal, medical applications multiply, Eric Topol, MD, Science, Sept 2023

Cubismi's "hypercube" technology uses our proprietary Multimodal AI methodologies, with first secured patents dating back to 2014-2015. Structured 3D-time patient virtual maps enable dense stitching of diverse types of data for specific tumors and other lesions. "Moving windows" (akin to CNN sliding windows) make classifications on stitched data based on comparisons to population data. "AI" neural networks can be used as the classifier. This results in granular precision predictions about tissues. For example, it enables potential vast information on tumor heterogeneity, which is critical need for cancer. "Hypercube" methods have initial independent validation by publications in leading journals and by company top data scientists. Cubismi's apps will enable further research and specific use cases validation for numerous types of cancer and other diseases.

DECISION INTELLIGENCE 'BEST ROUTES' DASHBOARDS

Decision Intelligence (DI) is a proven machine learning (ML) and “AI” analytics methodology to manage today’s new reality of ever-increasing decision complexity. When multiple individual decisions and/or algorithmic outputs are synthesized for improvement of a given outcome, it can be used to power continually improved outcomes through additional analysis, monitoring, feedback, and improvement of decision-making frameworks. It leverages various methods for improving, supporting, automating, and augmenting individual decisions within each larger decision-making framework. DI has been validated in domains such as mortgage approvals, Formula 1 racing, and Google Maps route optimization. Only by using DI analytics will we be able to assure AI tools are actually improving patient care outcomes. The first known clinical medicine DI use cases were used by the NHS in the UK for a COVID application.

LEARN MORE ABOUT OUR DECISION LINK FRAMEWORK

Re-imagine big data to imagine a better future, DIGITALLY TRANSFORMED.

CLOUD-BASED 3D-ANATOMY TIME INTERACTIVE VIRTUAL MAP

Backstage at RSNA 2022, Founder Interview

Join a community of fellow physicians and other stakeholders to help deliver a responsible and successful pathway for cloud-AI adoption.

Key stakeholders are working with us to develop the first Decision Intelligence pathways for radiology and digital health. Join us and gain access to our early dashboard apps for clinical researchers.

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