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Segmed AI

Segmed AI

Segmed AI is a real-world data platform focused on delivering high-quality, de-identified medical imaging data. It connects healthcare providers worldwide with researchers and developers through structured processing and a one-stop subscription service, aiming to accelerate medical AI development, clinical research, and medical device innovation.
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Medical imaging data platformDe-identified medical dataReal-world imaging dataData for medical AI developmentClinical research data supportDICOM data servicesMedical device R&D dataMedical data compliance platform

Features of Segmed AI

Provides de-identified medical imaging data from global partner healthcare institutions, covering DICOM images and radiology reports.
Supports multi-dimensional filtering and customization of datasets by body part, imaging modality, patient demographics, and more.
Enables rapid data discovery, preparation, and delivery via a self-serve platform, shortening the acquisition cycle.
End-to-end services including data governance, clinical research feasibility optimization, and real-world evidence analysis.
Platform integrates interoperability standards such as FHIR and DICOMweb for easier data integration and use.
Provides validated datasets suitable for regulatory submissions (FDA, CE, etc.), supporting product development and approval processes.
Features a large language model-based de-identification demonstration tool for processing textual medical reports.

Use Cases of Segmed AI

For AI healthcare companies developing disease diagnosis algorithms, to obtain structured imaging datasets for training and validation.
Pharmaceutical companies designing clinical trials can leverage its data to construct external control arms or identify patients.
Medical device manufacturers in the R&D phase need imaging data of specific modalities for testing and comparative analysis.
Academic research institutions conducting disease natural history or biomarker discovery studies require longitudinal real-world imaging data.
Life science teams in drug repurposing or post-market surveillance use platform data to generate evidence.
Healthcare organizations seeking to monetize their imaging data in a compliant manner can use the platform to authorize and de-identify processing.

FAQ about Segmed AI

QWhat is Segmed AI?

Segmed AI is a real-world medical imaging data platform focused on providing high-quality, de-identified imaging data to support medical AI development, clinical research, and medical device innovation.

QWhat type of data does the Segmed AI platform primarily provide?

The platform primarily provides de-identified medical imaging data, including DICOM images, associated radiology reports, and related structured metadata.

QHow long does it take to use Segmed AI data?

Through its self-serve technical platform, researchers can access data almost instantly, with customized datasets typically prepared and delivered within a few days.

QHow does Segmed AI ensure data security and compliance?

The platform prioritizes security and privacy, applying strict de-identification, and designing its processes to meet relevant regulatory requirements, including support for FDA-cleared products.

QWho is Segmed AI suitable for?

Primarily for pharmaceutical companies, medical device manufacturers, medical AI developers, academic research institutions, and healthcare organizations pursuing clinical research or data value realization.

QWhere does Segmed AI source its data from?

Data comes from partner healthcare institutions worldwide across multiple continents and countries to ensure patient population diversity.

QDoes Segmed AI offer free tools?

Yes, it offers a large-language-model-based de-identification demonstration tool for medical data, which can be used free of charge to process text-based medical reports.

QHow does Segmed AI help accelerate regulatory approval of medical products?

The platform provides validated datasets suitable for regulatory submissions and supports end-to-end data services from development to approval, helping to meet regulators' requirements for real-world evidence.

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