Project
Med-Fashion Forecast: Predictive Analytics for Healthcare Fashion
Overview
Analyzed trends in medical uniforms and accessories to forecast future popular items, combining sales data with social sentiment analysis.
Why It Matters
Understanding fashion trends in healthcare can lead to improved product offerings and patient satisfaction, merging functionality with style.
Outcome
Identified emerging trends in healthcare apparel, providing insights for manufacturers and retailers to align products with market demands.
Resources
Data Sources:
Kaggle Retail Datasets: Look for “clothing sales” or “fashion trend” datasets (can be repurposed to medical gear).
Google Trends API: Analyze interest in terms like “compression socks,” “scrub fashion,” etc.
Twitter or Reddit scraping: Use NLP on fashion/healthcare hashtags or subreddits.
Medical Apparel Brands: Check blogs from Figs, Jaanuu, or Nurse Mates for trends.
Bonus: Simulated B2B purchase data or interview nurses for qualitative insight.
Category:
Domain: Fashion Analytics / Functional Apparel Forecasting
Industry: Healthcare Apparel, RetailTech, Trend Analysis
Technical Specialization: Time Series Forecasting, Sentiment Analysis, Market Intelligence
