Dataset opportunity
Distalmotion — Medical Imaging Dataset Opportunity
Moderate medical imaging dataset held by Distalmotion, usable for Diagnostic AI and Computer Vision.
Score
67.1
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
49%
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
Global AI-based medical imaging market size was valued at $3.276 billion in 2024 and is projected to reach $96.82 billion by 2033, exhibiting a CAGR of 45.68% during the forecast period (2025–2033).
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-04
Can surgical robots fly? SS Innovations discusses challenges, solutions
therobotreport.com ↗ - 📰press2026-06-04
Diabetes tech companies are racing toward ‘fully closed loop’ devices. But automation comes with trade-offs.
medtechdive.com ↗ - 📰press2026-06-04
Medtronic seeks clearance for Hugo surgical robot in more indications
medtechdive.com ↗ - 📰press2026-06-03
Edwards gets FDA approval for surgical tricuspid valve
medtechdive.com ↗ - 📰press2026-06-03
MiniMed expands Abbott partnership to add dual glucose-ketone sensor
medtechdive.com ↗
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
High (proprietary)
Accessibility
Restricted
Legal
Mixed ownership — GDPR-sensitive (PII review)
Buyer persona
Medical-AI & diagnostic-imaging companies
Distalmotion possesses a rich Medical Imaging Dataset primarily of the Image modality, augmented by crucial supplementary data streams including event_streams, IoT_data, and medical_records. This comprehensive data collection is exceptionally well-suited for developing advanced Diagnostic AI solutions, enabling the identification of subtle patterns and anomalies that can significantly enhance diagnostic accuracy and facilitate earlier disease detection. The integration of diverse data types provides a holistic view, critical for training robust and context-aware AI models.
Despite the inherent challenges, such as managing sensitive patient information with strict GDPR/HIPAA implications, navigating data ownership complexities with hospitals/surgeons, and requiring complex agreements with multiple healthcare providers, the data remains immensely valuable. The global AI in medical imaging market, valued at billions and experiencing rapid growth, underscores the high demand for such datasets. This market potential justifies the investment in overcoming access complexities, as the data is pivotal for driving innovation in healthcare diagnostics and improving patient outcomes. ⚠ Diligence (valuable data, access to negotiate): Data contains sensitive patient information (GDPR/HIPAA implications).; Data ownership likely resides with hospitals/surgeons, requiring complex agreements.; Requires agreements with multiple healthcare providers for comprehensive datasets. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Distalmotion holds a proprietary, multi-modal dataset stemming from nearly 3,000 real-world robotic surgical procedures, encompassing crucial medical imaging, rich clinical outcome, and detailed device telemetry data. This unique combination directly addresses the urgent need for high-quality training data for Diagnostic AI and medical-AI companies, enabling the development of advanced algorithms in a global market projected to reach $96.82 billion by 2033. This dataset offers an unparalleled opportunity to accelerate innovation in the rapidly expanding AI-based medical imaging sector.
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 Rarity82
proprietary domain data
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 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 Demand95
The AI in medical imaging market, which relies heavily on these datasets for diagnostic AI, is projected to grow at a Compound Annual Growth Rate (CAGR) of 35.11% from 2026 to 2033, reaching USD 20.2 billion by 2033.
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility0
PII/regulated
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility0
medium difficulty, independent
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 evidence types, 3 hits
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License28
ownership=mixed, 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, 5 recent external signals — 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 Audit83
✓ good target — Distalmotion is a MedTech company that manufactures and sells robotic surgery systems, generating valuable medical imaging and operational data as a by-product of its core business, making it a good target for a data marketplace. Issues: While Distalmotion's employee count (227-230) falls within some SME definitions, its significant funding ($390M Series G) and global commercial presence suggest
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
This evidence represents device telemetry from Distalmotion's DEXTER robotic system, detailing operational parameters from 45 communicating nodes and extensive software, offering crucial insights for performance optimization and AI-driven robotic control.
Medical records / imaging
This core evidence confirms a substantial collection of medical imaging data from almost 3,000 patients treated with the DEXTER system across Europe and the U.S., providing clinically validated, real-world data essential for Diagnostic AI training and validation.
Event streams
This data type captures clinical outcome and patient journey information, including procedure details, operation times, demographic data, and post-operative complications, offering vital context for predictive analytics and understanding surgical efficacy.
Coverage
Scanned sources
Deliverable
Premium dataset report
Distalmotion Medical Imaging — a Moderate medical imaging dataset (Image modality) in the healthcare domain. Primary AI use-case: Diagnostic AI. Market signal: Global AI-based medical imaging market size was valued at $3.276 billion in 2024 and is projected to reach $96.82 billion by 2033, exhibiting a CAGR of 45.68% during the forecast period (2025–2033).. Investment score 67.1/100 (confidence 0.49). Recommended action: Data Sharing Agreement.