Role: AI Business Consultant
ClimaCare: AI Predictive Healthcare Platform, uses weather, COVID-19, and hospital data to forecast emergency demand, optimize resource allocation, and reduce hospital emergency waiting times.
As part of an independent project in collaboration with two major hospitals in Stockholm, I developed the concept and carried out data-driven analysis using real datasets from SMHI, Socialstyrelsen, Region Stockholm, Folkhälsomyndigheten and SKR. I explored how seasonal patterns — including temperature shifts, infection waves and public health indicators — correlate with spikes in emergency visits.
By cleaning, structuring and visualising the data, I identified clear correlations between temperature drops and increased demand for emergency care. Research from Harvard on the seasonal behaviour of COVID-19 further supported the potential of predictive modelling for improving hospital preparedness. The proposed solution used an AI forecasting model to support day-to-day decisions on staffing, medicine supply and bed capacity.
Early analysis suggested that accurate inflow predictions could reduce peaks in emergency congestion and help hospitals proactively manage resources during high-demand periods. A concept prototype was developed to illustrate how forecasts, alerts and recommended actions could be presented in a simple, decision-support dashboard.
Time-Series Analysis • Data Cleaning & Preparation • Correlation Analysis • Pattern Detection • Predictive Modelling Concept • Healthcare Demand Mapping • Data Visualisation Strategy
Tools:Python (pandas, numpy) • Tableau • SQL • Excel • Miro • Notion • Microsoft Copilot (analysis support) • Google Gemini Advanced (data summarisation) • ChatGPT+
Skills:AI Strategy • Predictive Modelling • Data Analysis • Healthcare Analytics • Data Visualisation • Resource Optimisation • Business Analysis • Statistical Research • Data-Driven Decision Making • Stakeholder Collaboration