Taiwo Oluwatosin Omolase/LinkedIn
Mar 5, 2026, 14:07
Taiwo Oluwatosin Omolase: How Data-Driven Risk Stratification Can Support Early Stroke Detection and Prevention
Taiwo Oluwatosin Omolase, Data Analyst at Kinplus Technologies, shared on LinkedIn:
”Stroke Risk Analytics Dashboard | Healthcare Data Project
I recently analyzed 5,109 patient records from the Kaggle Stroke Prediction Dataset to explore patterns in stroke occurrence.
Key Findings:
- Total Stroke Cases: 249 (4.87%)
- Average Stroke Age: 67.7 years
- Female patients recorded more stroke cases (141 vs 108 males)
- 73% of stroke patients had no diagnosed hypertension
- Age 60+ consistently showed stronger association with stroke occurrence.
What This Project Reinforced:
- Raw counts can be misleading in healthcare analytics.
- Risk interpretation requires subgroup rate calculations, not just frequency.
- For example, while a large number of stroke cases appeared in older non smokers without hypertension, this may reflect population distribution rather than elevated individual risk.
Tools Used:
Power BI | DAX
As a pharmacist with growing interest in healthcare analytics, I am particularly passionate about how datadriven risk stratification can support early detection and preventive medicine.
I welcome feedback from healthcare professionals and data scientists.”
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