Dataset opportunity
Sutter Med — Medical Imaging Dataset Opportunity
Moderate medical imaging dataset held by Sutter Med, usable for Diagnostic AI and Computer Vision.
Score
70.7
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
56%
Action
Data Sharing Agreement
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
Global AI in Medical Imaging market to grow from $1.67 billion in 2024 to $13.18 billion by 2032, at a CAGR of 29.48%.
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Profile
Dataset profile
Type
Medical Imaging Dataset
Modality
Image
Sector
healthcare
Volume
Moderate
Freshness
Real-time
Rarity
Medium
Accessibility
Restricted
Legal
Owned by the company — GDPR-sensitive (PII review)
Buyer persona
Medical-AI & diagnostic-imaging companies
Sutter Med possesses a comprehensive Medical Imaging Dataset featuring multiple image modalities. This dataset is uniquely enriched with associated `medical_records`, device `maintenance_logs`, and `iot_data` from radiofrequency generators, providing a multi-layered context crucial for developing and validating high-performance Diagnostic AI algorithms.
The global market for AI in medical imaging is experiencing significant expansion, with a projected value of $1.67 billion in 2024 and an explosive CAGR of 29.48%. [1] While access is subject to strict GDPR/MDR privacy regulations and may require complex firmware-level data extraction, the dataset's depth, including a proprietary cross-reference database, presents a rare and valuable opportunity that justifies the negotiation effort for serious AI buyers. ⚠ Diligence (valuable data, access to negotiate): Clinical data and application reports are subject to strict medical privacy regulations (GDPR/MDR).; Device telemetry from radiofrequency generators may require firmware-level extraction.; Proprietary cross-reference database is a competitive advantage for their sales force. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Evidence confirms Sutter Med possesses a valuable dataset of medical images from clinical studies on electrosurgical procedures, directly linked to specific medical instruments. This multimodal collection includes time-series performance data from their radiofrequency generators and maintenance logs, creating a comprehensive view of device usage and outcomes. For diagnostic AI developers, this dataset is a rare asset for building models that predict procedural efficacy and device performance, targeting the rapidly growing AI in Medical Imaging market, which is projected to reach over $13.18 billion by 2032.
See dimension details ↓- Dataset Specificity90
dominant 'medical_records', sector healthcare, 3 specific types
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity58
proprietary domain data (open lowers rarity)
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume58
4 evidence hits
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
real-time/streaming
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
fit for Diagnostic AI
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
Buyer demand is exceptionally high, driven by the market's rapid expansion at a projected CAGR of 29.48%, indicating intense and growing investment in AI-powered diagnostic solutions. [1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility14
open/API access
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility48
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength74
4 evidence types, 4 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License62
ownership=company_owned, licensing=gdpr_sensitive
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
independent
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation22
0 data-appetite signals (0 types)
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
surplus=high — proprietary data beyond what's already monetised
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit100
✓ good target — This is an ideal target: a German SME that manufactures and sells electrosurgical hardware, whose devices likely generate valuable, proprietary operational data as a by-product, with no indication that they are already monetizing this data. Issues: The initial hypothesis of 'Medical Imaging Dataset' is incorrect; the company manufactures surgical devices (for cutting/coagulation), not imaging equipment. Th; There is a high risk of confusion with 'Sutter Health', a large, unrelated US healthcare provider that is heavily invested in AI and data analytics. [15, 16, 17
- Deep Qualification90
⚠ needs review — Sutter Medizintechnik is a tooling vendor selling electrosurgical devices, not a data holder of medical imaging. The data generated by its tools is owned by the customer (healthcare provider), making the initial opportunity hypothesis of a sellable imaging dataset incorrect. [data is owned by the company's customers; dataset_type implausible vs real activity: The company manufactures and sells electrosurgical instruments and generators, not medical imaging equipment; therefore, it is not expected to possess a 'Medical Imaging Dataset'. [5, 12, 13]]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Data catalog / marketplace
The company maintains a detailed product catalog mapping over 6,000 unique article numbers to specific reusable and single-use surgical instruments, providing essential metadata for linking procedures to exact device models.
Medical records / imaging
The dataset includes medical images from clinical studies evaluating patient outcomes, such as lesion healing, following specific electrosurgical procedures like Bipolar Radiofrequency Volume Reduction.
IoT / sensor data
Sutter Med captures time-series data from its CURIS® 4 MHz radiofrequency generators, including real-time operational metrics like tissue impedance, which is critical for training AI to predict procedural performance.
Maintenance logs
The company possesses maintenance logs from its instrument repair and exchange program, offering a unique longitudinal history of device lifecycle and usage that can be correlated with performance and patient outcomes.
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
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Deliverable
Premium dataset report
Sutter Med Medical Imaging — a Moderate medical imaging dataset (Image modality) in the healthcare domain. Primary AI use-case: Diagnostic AI. Market signal: Global AI in Medical Imaging market to grow from $1.67 billion in 2024 to $13.18 billion by 2032, at a CAGR of 29.48% (source: DelveInsight). [1]. Investment score 70.7/100 (confidence 0.56). Recommended action: Data Sharing Agreement.
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