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Project Case Study

Enact Business Solutions / Private

Coronary Angiogram Dataset Cleaning

Rule-driven cleaning for coronary angiogram records and derived clinical features.

Track

Enact Business Solutions

Category

Data Engineering

Role

Role: Data Engineering Delivery

Status

Private

Year

2025

Overview

Problem, execution, and outcomes

Problem

Coronary angiogram records required normalization before reliable downstream grouping and analysis.

Execution

Applied clinical cleaning rules, severity normalization, derived feature generation, and validation checks.

Outcomes

Cleaned coronary angiogram fields.

Standardized severity and derived indicators.

Improved dataset readiness for analytics.

Proof and Metrics

Clinical rulesSeverity normalizationDerived features

Capability Proven: Domain-informed data quality engineering for specialized clinical datasets.

Confidentiality: Private healthcare workflow. Sensitive records are excluded.

Coronary Angiogram Dataset Cleaning project evidence visual
Healthcare Data Flow

Stack

PythonPandasClinical RulesData Validation

Tags

CoronaryAngiogramClinical Analytics

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