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Empowering Pathologists, Microbiologists and Researchers to Impact the growing cancer healthcare challenges. We Increase the speed, accuracy and consistency of disease diagnosis.
Empowering Pathologists, Microbiologists and Researchers to Impact the growing cancer healthcare challenges. We Increase the speed, accuracy and consistency of disease diagnosis.
About
We enable better, faster, more accurate, more informed decisions by discovering, interpreting, linking, simulating, and validating diverse data sources relevant to cancer detection.
Cloud Based software solution specifically designed to bring the benefits of Generative AI, Knowledge Engineering and Digital Pathology to pathologists, research laboratories and teaching hospitals.
Platform Components
Control Center
Data Manager
- Continual Enrichment of Data
- Human Genome
- NIH
- Proprietary Systems
Report Manger
Generates Comprehensive and coherent medical reports of a given medical image.
- Annotations
- Scheduled
- Ad HOC
Workflow Manager
- Minimize lost time, increased efficiency and revenues
- Significantly increase diagnostic capacity
- Optimize the diagnosis
Ecosystem integration Partners
- Agnostic
- Microscopes
- API’s
Health Care Providers Partner Network
- Hospital Management Systems- Patient’s charts
- Hospital Data / Images Feeds – Cytology, microbiology, urinalysis, pap smears, etc
- Provider Proprietary Systems
Knowledge Engine
- Dynamic exploration and discovery of diverse data sources relevant to multi-dimensional problems. (de-identified)
- We use a large quantity of pre-trained knowledge to help achieve greater efficacy, reliability, and generalization across diverse domains.
Foundational Model
- Federated, MMLLM (Multimodal Large Language Models) Learning
- Detailed Data Enrichment / Sharing
- Cloud Based Storage and Retrieval – provides full access to all records in a controlled and secure environment, 24 x 7
- Collaboration in real-time to all authorized users or experts on any internet enabled device
Our foundational model provides a solid base for various machine learning tasks by serving as the building blocks for more specialized models. MMLLM models integrate textual and visual data from pathology images, enhancing diagnostic capabilities and treatment recommendations. Our federated learning approach ensures data privacy and model security across distributed healthcare systems.
By exploring complex data from diverse sources (including, but not limited to, real world evidence, structured databases, unstructured sensor feeds, and external data streams) we uncover valuable insights from sources that were once invisible to conventional AI, ML, and Large Language Models (LLMs).
Our digital twin ecosystem uniquely grows and improves by leveraging previous analyses, expanding the scope of discovery, and increasing evidence quality.
Learn more about how genomics, Knowledge Engineering, and our biomimetic digital twin ecosystem, can precisely delineate the molecular mechanism of diseases, predicting severity, conducting virtual clinical trials, and facilitating the swift identification of new, effective therapies for treatment.
The Research Platform enhances decision-making processes, speeds the research process, and improves the likelihood that no crucial information is overlooked in the pursuit of cancer solutions.
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