Witness-Data-Factory/surgical-1k

WITNESS DATA Factory provides synthetic, regulatory‑grade medical text datasets so clinical AI teams can develop and validate models without touching real patient data. Each corpus is generated by a multi‑model medical LLM ensemble, gated by strict consensus and schema versioning, and designed to plug directly into enterprise model governance and documentation workflows. We focus on multi‑domain healthcare (including oncology, cardiology, neurology, endocrinology, radiology, pathology, surgical, pharmacology, and rare disease) to support robust evaluation across diverse clinical scenarios. --- license: cc-by-4.0 task_categories: - text-classification - token-classification - question-answering language: - en tags: - medical - healthcare - synthetic-data - nlp - surgical - clinical-ai - hipaa-compliant - medical-nlp - healthcare-ai - electronic-health-records - labeled-data pretty_name: Surgical Medical Dataset (1K Free Sample) size_categories: - 1K<n<10K --- # 9-domain synthetic medical catalog: oncology, cardiology, neurology, endocrinology, radiology, pathology, surgical, pharmacology, rare disease. --- # Surgical Medical Dataset — 1,000 Record Free Sample > **Enterprise-grade synthetic medical data. Zero PHI. 100% HIPAA-compliant.** [](https://creativecommons.org/licenses/by/4.0/) --- ## 📊 Quality Metrics | Metric | Score | Industry Benchmark | |--------|-------|--------------------| | **Trinity Consensus Score** | 98.0% | 85–92% typical | | **Inter-Annotator Agreement** | 0.97 | 0.75–0.85 typical | | **Macro F1** | 0.97 | 0.80–0.90 typical | | **PHI Present** | None | — | | **Generation Method** | 3-LLM Ensemble | Single model typical | --- ## 🚀 What's Included (Free) - **1,000 clinically-structured synthetic surgical records** - Full label taxonomy with confidence scores per record - Consensus scores per record (filter by your own threshold) - Structured Parquet format (load with 🤗 `datasets` in one line) - Zero PHI — safe for unrestricted research and commercial use --- ## ⚡ Quick Start ```python from datasets import load_dataset # Load free 1K sample ds = load_dataset("Witness-Data-Factory/surgical-1k", split="train") print(ds[0]) # Filter by quality gate high_quality = ds.filter(lambda x: x["consensus_score"] >= 0.97) print(f"Records passing 97% gate: {len(high_quality)}") # Export to pandas df = ds.to_pandas() df.to_csv("surgical_sample.csv", index=False) ``` --- ## 🗂 Dataset Schema ```json { "record_id": "uuid-v4", "domain": "surgical", "category": "Specific clinical subcategory", "note_type": "Clinical note type", "patient_age": 42, "patient_gender": "Female", "primary_label": "diagnosis", "labels": { "primary": "diagnosis", "category": "Subcategory name", "confidence": 0.972 }, "consensus_score": 0.972, "inter_annotator_agreement": 0.941, "macro_f1": 0.963, "model_scores": { "llama3.3": 0.975, "mistral": 0.968, "qwen2.5": 0.972 }, "passes_quality_gate": true, "generation_method": "Trinity_Ensemble_v2", "phi_present": false, "hipaa_compliant": true } ``` --- ## 💰 Upgrade to Production Scale This 1K sample is your **proof-of-concept dataset**. When you're ready to train production models: | Tier | Records | Price | Per-Record | Best For | Buy | |------|---------|-------|------------|----------|-----| | **Starter** | 10,000 | **$1,999** | $0.20 | Pilot deployment, MVP | [Buy Now →](https://witness-data-factory.onrender.com/pay/surgical-10k) | | **Production** | 50,000 | **$7,999** | $0.16 | Model training, Series C+ | [Buy Now →](https://witness-data-factory.onrender.com/pay/surgical-50k) | | **Enterprise** | 250,000 | **$29,999** | $0.12 | FDA-track, clinical AI | [Buy Now →](https://witness-data-factory.onrender.com/pay/surgical-250k) | | **Strategic** | 1,000,000 | **$99,999** | $0.10 | Multi-year partnerships | [Contact Sales →](mailto:[e-mail]) | ### 🎁 Multi-Domain Bundles | Bundle | Contents | Price | Discount | |--------|----------|-------|---------| | **3-Domain Bundle** | 50K × 3 domains of choice | **$19,999** | 17% off | | **Complete Collection** | 50K × all 8 specialties | **$49,999** | 22% off | [View All Bundles →](https://witness-data-factory.onrender.com/pay/complete-collection-8x50k) > **Delivery:** Instant checkout → Full dataset delivered within 24 hours. --- ## 🏥 Why WITNESS DATA FACTORY? ### Speed Your research timeline shouldn't wait 3–6 months for custom data generation. Production datasets delivered in **under 24 hours** from purchase. ### Quality - **98.0% consensus** vs. 85–92% industry standard - 3-LLM ensemble eliminates single-model hallucination bias - Every record validated through Trinity quality gates before delivery ### Scale - Proven on **100M+ record PostgreSQL infrastructure** - Billion-record architecture ready for enterprise contracts - Multi-domain coverage: Oncology, Cardiology, Rare Disease, Mental Health, Pediatrics, Radiology, Pathology, Emergency Medicine ### Compliance - **Zero PHI** — 100% synthetic, no de-identification liability - HIPAA-compliant by architecture - CC BY 4.0 license — commercial use permitted --- ## 📚 Citation ```bibtex @dataset{witness_data_factory_surgical_2026, title = {Surgical Synthetic Medical Dataset}, author = {WITNESS DATA FACTORY}, year = {2026}, publisher = {HuggingFace}, url = {https://huggingface.co/datasets/Witness-Data-Factory/surgical-1k} } ``` --- ## 🤝 Contact | Channel | Address | |---------|---------| | Sales & Licensing | [[e-mail]](mailto:[e-mail]) | | Technical Support | [[e-mail]](mailto:[e-mail]) | | All Datasets | [huggingface.co/Witness-Data-Factory](https://huggingface.co/Witness-Data-Factory) | --- *Powered by **WITNESS DATA FACTORY** — Medical AI Data Labeling at Scale*WITNESS DATA Factory 提供符合监管标准的合成医疗文本数据集，使临床AI团队无需接触真实患者数据即可开发和验证模型。每个语料库均由多模型医疗大语言模型（Large Language Model，LLM）集成生成，通过严格的共识机制与模式版本控制进行把关，并可直接嵌入企业级模型治理与文档工作流。我们聚焦多领域医疗场景（涵盖肿瘤学、心脏病学、神经病学、内分泌学、放射学、病理学、外科学、药理学与罕见病），以支持在多样化临床场景下开展可靠的模型评估。 --- 许可证: cc-by-4.0 任务类别: - 文本分类 - 词元分类（Token Classification） - 问答系统 语言: - 英语 标签: - 医疗 - 医疗健康 - 合成数据 - 自然语言处理（Natural Language Processing，NLP） - 外科 - 临床AI - 符合HIPAA（健康保险流通与责任法案，Health Insurance Portability and Accountability Act）标准 - 医疗自然语言处理 - 医疗AI - 电子健康记录（Electronic Health Records，EHR） - 标注数据 美观名称: 外科医疗数据集（1000条免费样本） 规模类别: 1000 < 样本数 < 10000 --- # 9领域合成医疗数据集目录：肿瘤学、心脏病学、神经病学、内分泌学、放射学、病理学、外科学、药理学与罕见病。 --- # 外科医疗数据集——1000条免费样本 > **企业级合成医疗数据。无受保护健康信息（Protected Health Information，PHI）。100%符合HIPAA标准。** [](https://creativecommons.org/licenses/by/4.0/) --- ## 📊 质量指标 | 指标 | 得分 | 行业基准 | |--------|-------|--------------------| | **三一共识评分（Trinity Consensus Score）** | 98.0% | 典型值为85%–92% | | **标注者间一致性（Inter-Annotator Agreement）** | 0.97 | 典型值为0.75–0.85 | | **宏F1值（Macro F1）** | 0.97 | 典型值为0.80–0.90 | | **含受保护健康信息** | 无 | — | | **生成方法** | 3个大语言模型集成 | 典型为单模型 | --- ## 🚀 免费包含内容 - **1000条临床结构化合成外科病历** - 每条样本均包含完整的标签分类体系与置信度分数 - 每条样本附带共识评分（可按自定义阈值筛选） - 结构化Parquet格式（可通过🤗`datasets`库一行代码加载） - 无受保护健康信息——可安全用于无限制的研究与商业用途 --- ## ⚡ 快速入门 python from datasets import load_dataset # 加载免费1000条样本 ds = load_dataset("Witness-Data-Factory/surgical-1k", split="train") print(ds[0]) # 按质量门限筛选 high_quality = ds.filter(lambda x: x["consensus_score"] >= 0.97) print(f"通过97%门限的样本数: {len(high_quality)}") # 导出为pandas数据框 df = ds.to_pandas() df.to_csv("surgical_sample.csv", index=False) --- ## 🗂 数据集架构 json { "record_id": "uuid-v4", "domain": "surgical", "category": "Specific clinical subcategory", "note_type": "Clinical note type", "patient_age": 42, "patient_gender": "Female", "primary_label": "diagnosis", "labels": { "primary": "diagnosis", "category": "Subcategory name", "confidence": 0.972 }, "consensus_score": 0.972, "inter_annotator_agreement": 0.941, "macro_f1": 0.963, "model_scores": { "llama3.3": 0.975, "mistral": 0.968, "qwen2.5": 0.972 }, "passes_quality_gate": true, "generation_method": "Trinity_Ensemble_v2", "phi_present": false, "hipaa_compliant": true } --- ## 💰 升级至生产级规模 本1000条样本为您的**概念验证数据集**。当您准备好训练生产级模型时： | 套餐等级 | 样本数量 | 价格 | 单条样本成本 | 适用场景 | 购买链接 | |------|---------|-------|------------|----------|-----| | **入门版** | 10,000 | **$1,999** | $0.20 | 试点部署、最小可行产品（Minimum Viable Product，MVP） | [立即购买 →](https://witness-data-factory.onrender.com/pay/surgical-10k) | | **生产版** | 50,000 | **$7,999** | $0.16 | 模型训练、C轮及以上融资阶段 | [立即购买 →](https://witness-data-factory.onrender.com/pay/surgical-50k) | | **企业版** | 250,000 | **$29,999** | $0.12 | 可追踪FDA流程的临床AI项目 | [立即购买 →](https://witness-data-factory.onrender.com/pay/surgical-250k) | | **战略版** | 1,000,000 | **$99,999** | $0.10 | 多年合作项目 | [联系销售 →](mailto:[e-mail]) | ### 🎁 多领域套餐 | 套餐 | 包含内容 | 价格 | 折扣力度 | |--------|----------|-------|---------| | **3领域套餐** | 自选3个领域，每个领域50,000条样本 | **$19,999** | 享17%折扣 | | **完整合集** | 8个专科领域，每个领域50,000条样本 | **$49,999** | 享22%折扣 | [查看全部套餐 →](https://witness-data-factory.onrender.com/pay/complete-collection-8x50k) > **交付方式**：即时结账→24小时内交付完整数据集。 --- ## 🏥 为何选择WITNESS DATA Factory？ ### 交付速度 您的研究进度不应因定制数据生成而等待3至6个月。生产级数据集自购买起**24小时内即可交付**。 ### 数据质量 - **98.0%的共识评分**，而行业标准为85%–92% - 采用3个大语言模型集成，可消除单模型产生的幻觉偏差 - 所有样本在交付前均通过三一质量门限验证 ### 规模能力 - 已在**超1亿条记录的PostgreSQL基础设施**上验证可行 - 支持十亿级记录的架构，可满足企业级合同需求 - 覆盖多领域医疗场景：肿瘤学、心脏病学、罕见病、精神卫生、儿科学、放射学、病理学与急诊医学 ### 合规性 - **无受保护健康信息**——100%合成数据，无需承担去标识化相关责任 - 架构层面符合HIPAA标准 - 采用CC BY 4.0许可证，允许商业使用 --- ## 📚 引用信息 bibtex @dataset{witness_data_factory_surgical_2026, title = {Surgical Synthetic Medical Dataset}, author = {WITNESS DATA FACTORY}, year = {2026}, publisher = {HuggingFace}, url = {https://huggingface.co/datasets/Witness-Data-Factory/surgical-1k} } --- ## 🤝 联系方式 | 渠道 | 联系方式 | |---------|---------| | 销售与许可 | [[e-mail]](mailto:[e-mail]) | | 技术支持 | [[e-mail]](mailto:[e-mail]) | | 全部数据集 | [huggingface.co/Witness-Data-Factory](https://huggingface.co/Witness-Data-Factory) | --- *由**WITNESS DATA Factory**提供支持——大规模医疗AI数据标注服务*