Pediatric Febrile Neutropenia Care Pathway Constraint Evaluation Dataset
#clinical constraint verification #care pathway compliance assessment #conflict detection #pediatric febrile neutropenia management #clinical care pathway evaluation #pediatric patient safety assessment
- 5000
- 0.4GB
- JSON
- CATL
MOBIUSI INC
Updated:2026-10-19
AI Analysis & Value Prop
This evaluation dataset represents pediatric febrile neutropenia cases in JSON, recording fever and blood count information, risk stratification rationale, comorbidities, allergy history, and proposed management pathways, alongside applicable pathway rules and expected conflict points. It supports checks of whether risk classification, treatment plans, investigation requirements, and disposition comply with pathway constraints, as well as model evaluation and error analysis in pediatric hematology and oncology. It is intended for research and evaluation and should not replace clinical judgment or current care guidelines.
Dataset Insights
Sample Examples
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Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| case_record | object | Original JSON input containing the patient's clinical facts, proposed care, applicable pathway rules, and expected conflicts. |
| risk_validation | object | Computed assessment of whether the recorded risk category is supported by the clinical inputs and pathway rules. |
| overall_validation | object | Final computed benchmark outcome and concise summary of pathway consistency. |
| management_validation | object | Computed checks of proposed treatment, allergy compatibility, required investigations, and disposition. |
| pathway_conflict_analysis | object | Computed comparison of observed pathway discrepancies with the benchmark's expected conflict points. |
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 case information does the dataset contain?
- Cases are organized as JSON and cover fever and blood count information, risk stratification rationale, comorbidities, allergy history, proposed management pathways, applicable rules, and expected conflict points. Refer to the accompanying field descriptions for the specific schema.
- Which capabilities can this dataset evaluate?
- It can assess whether a model uses case details and pathway rules to validate risk classification, check treatment, allergy compatibility, required investigations, and disposition, and compare detected discrepancies with expected conflict points.
- How large is the dataset, and what quality information is available?
- The information provided does not specify the case count or detailed quality metrics. The data is structured as JSON and includes rules and benchmark outcomes for validation; review the delivered sample, field descriptions, and available quality information before use.
- How can I obtain the dataset, and what are the licensing terms?
- Availability and licensing terms should be confirmed on the product page or with the data provider. The dataset is intended for model research, benchmark evaluation, and error analysis, not as a standalone basis for clinical care.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2026,
title={Pediatric Febrile Neutropenia Care Pathway Constraint Evaluation Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/90947fc4c40cce5931b0c1e3e546b607},
urldate={2026-10-12},
keywords={pediatric febrile neutropenia,pediatric hematology oncology dataset,clinical pathway constraint verification,medical AI evaluation data,risk stratification validation,pediatric care pathways,clinical decision evaluation,JSON case data},
version={1.0}
}Using this in research? Please cite us.
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