Building a Medical AI Model from Scratch Part 2: Data Visualization for Healthcare AI - EDA скачать в хорошем качестве

Building a Medical AI Model from Scratch Part 2: Data Visualization for Healthcare AI - EDA

Part 2 of our Thyroid Cancer Recurrence Prediction Series! In this video, we explore categorical features through beautiful, informative visualizations: ✅ Gender distribution and its relationship with recurrence ✅ Smoking habits and cancer outcomes ✅ Cancer staging patterns ✅ Risk classification analysis What You'll Learn: Creating professional count plots with Seaborn Calculating recurrence rates across categories Interpreting medical data visualizations Best practices for clean, publication-ready plots Resources: Dataset: http://archive.ics.uci.edu/dataset/91... GitHub Code: [Your repo link] Color Scheme Guide: [Link to color palette] Required Libraries: pandas, numpy, matplotlib, seaborn Timestamps: 0:00 - Introduction & Recap 01:00 - Gender Distribution Analysis 11:10 - Smoking vs Recurrence 20:00 - Cancer Stage Distribution 21:50 - Risk Category Analysis 24:30 - Summary Table 📺 Series Playlist:    • Building a Medical AI Model from Scratch  ...   ⬅️ Previous: Part 1 - Data Loading & Setup ➡️ Next: Part 3 - EDA Continuous Features #ThyroidMLSeries #DataVisualization #medicalaid #datascience #studyabroad #coding #python #programming #researchposition --- Key Takeaways: Risk categories show clear correlation with recurrence Stage progression indicates increased recurrence rates Consistent visualization styling improves professionalism EDA reveals patterns that guide model development Discussion Questions: 1. Which categorical feature surprised you most? 2. What other visualizations would you create? 3. How might these features interact? Songs: Measured Paces - Kevin MacLeod Drop your answers below! 👇