Dataset opportunity
Neocis — Medical Imaging Dataset Opportunity
Moderate medical imaging dataset held by Neocis, usable for Diagnostic AI and Computer Vision.
Score
68.3
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
Global AI in medical imaging market = $5.86 billion in 2024, CAGR 28.32% (source: Collective Minds)
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-02
Petal Surgical adds more funding for incisionless surgical robot
therobotreport.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
Neocis possesses a rich Medical Imaging Dataset (primarily Image modality) complemented by image_collection, iot_data, knowledge_base, and medical_records. This multimodal medical dataset is exceptionally valuable for Diagnostic AI applications, as it provides a comprehensive foundation for training AI models to identify complex patterns, make accurate predictions, and assist in diagnoses, particularly within the dental healthcare sector. The integration of diverse data types significantly enhances AI model accuracy, generalizability, and robustness.
The AI in medical imaging market is experiencing substantial growth, valued at approximately $5.86 billion in 2024 and projected to reach $20.40 billion by 2029, demonstrating a robust CAGR of 28.32%. Despite inherent challenges such as managing patient health information (PHI), adhering to strict privacy regulations like HIPAA, and navigating potentially shared data ownership with dental clinics, the rarity and high demand for such high-quality, annotated medical imaging data for AI training underscore its significant business value. This data is critical for developing AI solutions that improve diagnostic precision and efficiency, ultimately leading to better patient outcomes. ⚠ Diligence (valuable data, access to negotiate): Data involves patient health information (PHI) and is subject to strict privacy regulations (e.g., HIPAA in the US).; Data ownership may be shared or complex with dental clinics using the Yomi system.; Regulatory hurdles for medical device data sharing. · corporate: independent.
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
Neocis demonstrably possesses a proprietary medical imaging dataset of high rarity, primarily comprising CBCT scans and related dental implant data, accumulated from nearly 100,000 procedures since 2016. This rich, real-world evidence is exceptionally valuable for Medical-AI & diagnostic-imaging companies seeking to develop advanced diagnostic AI solutions, particularly within the rapidly expanding global AI in medical imaging market, projected at $5.86 billion in 2024. The dataset's depth and clinical context offer a unique opportunity to accelerate innovation in a critical healthcare sector.
See dimension details ↓- Buyer Demand95
The global AI in diagnostics market, which relies heavily on medical imaging datasets, is projected to grow from USD 7.03 billion in 2025 to USD 209.63 billion by 2034, exhibiting a Compound Annual Growth Rate (CAGR) of 46.06%.
How strongly AI builders and companies are likely to want this data, based on market signals. - 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 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. - 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
high 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 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, 1 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 Audit58
⚠ review — Neocis is excluded as a target because its core business involves selling a robotic system with integrated AI software that provides intelligence derived from medical imaging data, which is explicitly against the ICP. Issues: Company's core business is selling AI software/intelligence as part of its product (YomiPlan AI within the Yomi robotic system), which is an exclusion criterion; While the employee count (110-218) might suggest an SME, the significant total funding ($180M-$237M)
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 confirms Neocis collects Time Series data on the operational mechanics of its Yomi S robotic system, detailing parameters like speed and torque during implant placement, which is valuable for optimizing surgical robotics and enhancing procedural precision.
Medical records / imaging
This clearly indicates Neocis possesses a substantial medical imaging dataset derived from nearly 100,000 dental implant procedures since 2016, providing a robust foundation for training diagnostic AI models in dental applications.
Image collection
This confirms Neocis owns proprietary medical image data from CBCT scans, featuring machine learning-driven segmentation of critical anatomy, which is highly relevant for developing advanced AI segmentation and surgical planning tools.
Knowledge base / docs
This points to Neocis having access to clinical study data and reports that detail the significant efficiency benefits of its Yomi Robotic System, offering crucial context for AI model validation and understanding real-world clinical performance.
Coverage
Scanned sources
Deliverable
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