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dmwaura-arch/breast-cancer-dashboard-powerbi

Domaine:

healthcare

Type de record:

project
Créateur:
dmw
Hôte:
Interactive Power BI dashboard analyzing breast cancer burden, diagnosis patterns, and outcomes across regions in Kenya. # Breast Cancer Surveillance Dashboard — Kenya ## Project Overview This project presents an interactive Power BI dashboard designed to analyze breast cancer burden, diagnosis patterns, treatment outcomes, and geographic distribution across regions in Kenya. The dashboard supports data-driven decision-making for early detection, resource allocation, and improved patient outcomes. The analysis uses a synthetic dataset representing 15,000 patient records to simulate real-world clinical and public health reporting scenarios. --- ## Objectives The main objectives of this project were to: * Analyze the distribution of breast cancer cases across regions and counties * Assess early versus late-stage diagnosis patterns * Examine demographic characteristics such as age and gender * Evaluate treatment outcomes and survival patterns * Identify geographic disparities in disease burden * Demonstrate end-to-end data analytics workflow using Power BI --- ## Tools and Technologies * **Power BI** — Data modeling, visualization, and dashboard development * **Microsoft Excel / CSV** — Data storage and preprocessing * **DAX (Data Analysis Expressions)** — Measures and calculated columns * **GitHub** — Portfolio documentation and version control --- ## Dataset Description The dataset contains **15,000 synthetic patient records** representing breast cancer cases across Kenya. ### Key Variables * Patient ID * Age * Gender * Region and County * Cancer Type * Cancer Stage * Stage Category (Early vs Late) * Tumor Size * Receptor Status * Treatment Type * Survival Status * Recurrence Status * Histology Confirmation * Diagnosis Date --- ## Dashboard Pages ## Dashboard Preview ### 1. Overview Provides a summary of total cases, early and late-stage diagnosis rates, and overall trends in breast cancer burden. --- ### 2. Early vs Late Diagnosis Analyzes patterns of early and late-stage diagnosis across regions and age groups to identify areas requiring improved screening a …

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github.com