Daniel Callbo

Short presentation

I work on the health-economic evaluation of AI-based ECG diagnostics in EmergAI — producing evidence on whether such diagnostics are cost-effective and should be adopted.

Keywords

• health economics
• cost-effectiveness analysis
• cost-utility analysis
• economic evaluation
• artificial intelligence
• machine learning
• ECG
• myocardial infarction
• register data
• systematic review
• bootstrapping
• multiple imputation
• R
• mental health economics

Biography

My background is in economics. I hold a master's degree in finance and worked for a few years in real estate and finance. I then completed a master's in public health with a focus on health economics at Uppsala University, where I carried out a trial-based cost-utility analysis in mental health using methods such as bootstrapping and multiple imputation in R. Since 2026 I have been a research assistant on the EmergAI project.

Research

My work concerns the health-economic side of AI-based ECG diagnostics. Within EmergAI I am conducting a register-based cost-effectiveness analysis of AI-assisted ECG interpretation for detecting myocardial infarction, drawing on Swedish national health-data registers, and a systematic review of published health-economic evaluations in the field. A recurring theme is building the analysis on observed patient-level outcomes from Swedish registers rather than modelled assumptions. More broadly, my interests include trial-based health-economic evaluations, quantifying uncertainty and handling missing data, analysis in R, and health economics in mental health. I want to contribute an economic dimension to health and produce evidence to support decision-making in care and policy.