Neurosurgical Procedure Sequence Constraint Evaluation Dataset

#sequence constraint verification #procedural error detection #workflow conflict analysis #neurosurgical workflow evaluation #surgical procedure safety assessment #clinical workflow compliance

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-11-04

AI Analysis & Value Prop

This JSON-structured benchmark represents neurosurgical procedure steps and their prerequisites, dependencies, incompatibilities, and ordering constraints, alongside candidate sequences and reference violation labels. It supports evaluation of a model’s ability to detect ordering errors, missing dependencies, and constraint conflicts, and is designed for structured constraint verification and domain benchmarking.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
candidate_sequence	array	The proposed ordered sequence of procedure step identifiers to be checked against the defined constraints.
procedure_constraints	object	The defined procedure steps and their prerequisite, dependency, incompatibility, and ordering constraints.
constraint_check_summary	object	A computed summary of whether the candidate sequence satisfies the procedure constraints.
reference_violation_labels	array	The benchmark-provided standard labels identifying constraint violations in the candidate sequence.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the benchmark contain?: The JSON data includes procedure steps and their prerequisites, dependencies, incompatibilities, and ordering constraints. It also provides candidate sequences, reference violation labels, and a constraint-check summary.

Which model capabilities can it evaluate?: It can support evaluation of whether a model detects step-order errors, missing prerequisite dependencies, and conflicts between incompatible operations, and can help compare model outputs with benchmark labels. Results depend on the model, evaluation method, and data usage.

How can I obtain and use the data?: Use the delivery method provided on the product page or data platform, and follow the accompanying JSON structure and documentation for parsing and evaluation. The information provided does not specify dataset size or file delivery details, so check the product listing before purchase.

Is this data suitable for clinical surgical guidance?: No. It is intended for model evaluation, research, and educational use, and does not replace validated clinical workflows, professional medical judgment, or surgical guidance. Check the product listing for the applicable license terms; no specific license is provided in the available information.

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Cite this Work

@dataset{Mobiusi2026,
  title={Neurosurgical Procedure Sequence Constraint Evaluation Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/756f67416f8c4cf483b84da18b5a04cb},
  urldate={2026-10-13},
  keywords={neurosurgery evaluation dataset,surgical workflow data,procedure step ordering,constraint verification dataset,medical AI benchmark,workflow dependency reasoning,surgical operation conflicts,JSON benchmark data},
  version={1.0}
}

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