Telepathology Platform

AI-Assisted Pathology Image Assessment for Modern Telepathology

The ROSEAId cloud-based platform provides tools for pathology image review, collaboration, and workflow management, enabling secure access to cases across devices and locations.

Regulatory Notice: Certain ROSEAId platform features and AI-enabled capabilities are investigational and intended for research use only. These features have not been cleared or approved by the U.S. Food and Drug Administration for diagnostic use.

AI-Assisted Pathology Image Assessment for Modern Telepathology

The ROSEAId cloud-based platform provides tools for pathology image review, collaboration, and workflow management, enabling secure access to cases across devices and locations.

About

Your Gateway to Advanced Telepathology Our AI-powered platform is a suite of modular solutions supporting education, pharmaceutical research, pathology image management, and laboratory workflows. Our flexibility, customization and scalability ensure our solution aligns perfectly with your unique requirements, supporting operational efficiency and collaborative pathology workflows

Holistic Approach to Various Challenges

Pathologists face operational and workflow challenges and operational efficiencies from navigating complex regional regulations to managing costly operations. Practitioners struggle with limited access to essential pathology tools and slow second opinions leading to delayed case reviews. The logistics of handling glass slides poses additional hurdles, affecting both the security and affordability of work. Simultaneously, data management coupled with high expenses for storage, review and retrieval further complicate the situation. Our solutions address these pressing issues providing streamlined and cost-effective solutions, empowering healthcare professionals to improve workflow efficiency, speed the process and support laboratory operations and collaboration.

Research Platform Components

Control Center

A centralized platform to manage, access, review, retrieve, and organize pathology image data and associated records.

Data Manager

Continual Enrichment of Data
Images, videos
Proprietary Systems

Report Manger

Generates comprehensive research summaries, image annotations, and laboratory documentation associated with pathology images.

Annotations
Scheduled
Ad HOC

Workflow Manager

Minimize lost time, increased efficiency and revenues
Significantly increase analytical throughput
Streamlines image review and laboratory workflow processes

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

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
Secure collaboration in real-time among authorized users and research teams

Use Cases

ROSEAId, Inc. and the University of Texas Health Sciences Center (UTHealth), Houston, Texas, combine their expertise in a collaborative effort to optimize the precision and scope of pathology research, overcoming challenges posed by intricate data sets and diverse structural complexities. Details on a few mentioned use cases are provided below.

ROSEAId explored Pancreatic Solid Lesions (PSL), training ML models with 1,200 images, refining image acquisition and ML processes. Followed by initiation in subsequent stages of single-cell identification, amended labelling, development of list of cell types and multi cell scenario capturing diverse combinations in pancreatic lesions. The model demonstrated its capabilities achieving high-rate accuracy in a blind test.

Preliminary Study Draft and Unified ModelIn preliminary investigational studies, the underlying algorithm demonstrated promising concordance with expert-reviewed assessments. These findings are research observations and have not been reviewed or cleared by the FDA for diagnostic use.

Subepithelial Lesions (GI) and Lung Lesions (CT-Guided EBUS) comprehensive study was completed affirming the effectiveness of the unified model with 93.25% accuracy.

Why Choose ROSEAId for Your Pathology Solutions ?

Our platform addresses today’s pathology workflow challenges by supporting productivity, operational efficiency, and collaborative review processes. Designed to streamline laboratory workflows, the platform helps reduce administrative complexity, improve access to high-definition pathology images, and enhance data organization across distributed teams. ROSEAId also supports quality assurance, education, retrospective analysis, and research initiatives by providing secure access to historical case information and associated documentation.

Conclusion

ROSEAId, Inc. is committed to advancing pathology workflows through technology, innovation, and strategic collaboration. We have developed AI-ROSE, a cloud-based platform designed to support pathology image management, remote collaboration, and workflow efficiency. Our long-term vision is to explore innovative technologies that may further streamline pathology workflows, image management, and collaborative review processes, with future capabilities remaining subject to research, validation, and applicable regulatory clearances.

Transforming Pathology with AI into the
Digital Future

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