Thoracoscopic Lung Resection Step Constraint Verification Benchmark

#surgical step verification #sequence constraint checking #omission and conflict detection #thoracoscopic lung surgery #surgical workflow verification #surgical patient safety assessment

5000
0.4GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This benchmark represents case context, observed surgical step sequences, and procedural constraints for thoracoscopic and robot-assisted lung resection in structured JSON. It provides validity judgments and specific violation results covering missing required steps, ordering conflicts, and unmet prerequisites. The data supports evaluation of models' thoracic surgical procedural knowledge and constraint-checking capabilities, as well as medical AI benchmarking and surgical workflow research.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
is_valid	boolean	Whether the observed sequence satisfies all supplied ordering, prerequisite, and required-step constraints.
case_context	object	The procedure and resection context provided as input for validating the surgical sequence.
constraint_set	array	The input constraints specifying required steps, precedence relations, and prerequisite conditions.
observed_sequence	array	The ordered list of surgical steps checked against the procedural constraints.
validation_summary	string	A concise account of the overall constraint-checking result, including relevant sequence conflicts or omissions.
ordering_violations	array	Detected violations of must-precede constraints, including the observed positions of the affected steps.
missing_required_steps	array	Required surgical steps that are absent from the observed sequence.
precondition_violations	array	Detected instances in which a step was performed before its required prerequisite.

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 dataset contain?: Structured JSON records include lung resection case context, observed step sequences, procedural constraints, validity judgments, and results such as ordering violations, missing required steps, and precondition violations.

Which capabilities can this benchmark evaluate?: It can assess whether models check surgical steps against precedence relations, required-step rules, and prerequisites, and identify conflicts or omissions in a workflow.

How can I obtain the data, and what are the licensing terms?: Check the dataset product page or contact the provider for available versions, delivery options, and licensing terms. Before use, verify the permitted scope and applicable privacy and medical data handling requirements.

Can this data be used for clinical decision-making?: This benchmark is intended for model evaluation, research, and surgical workflow analysis. It should not replace professional medical judgment, clinical standards, or individualized patient care decisions.

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Cite this Work

@dataset{Mobiusi2026,
  title={Thoracoscopic Lung Resection Step Constraint Verification Benchmark},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/cbdf6aaf631c6f7eed0d9d8367e6f48e},
  urldate={2026-10-13},
  keywords={thoracoscopic lung resection dataset,thoracic surgery benchmark,surgical step constraint verification,lung resection workflow evaluation,robot-assisted surgery data,medical AI evaluation,procedural knowledge benchmark,surgical order detection},
  version={1.0}
}

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