Anne de Hond

Anne de Hond is an Assistant Professor in the Data Science Program at UMC Utrecht’s Julius Center, specializing in the responsible development, validation, and implementation of AI algorithms in healthcare. Her work bridges machine learning and clinical decision-making, with applications in mortality prediction, depression risk assessment, and ICU workflow optimization.

Her research focuses on enhancing the reliability and fairness of AI models in clinical settings. Key projects include predicting hospital admissions at emergency departments, assessing depression risk in oncology patients, and analyzing the practical implementation of AI software in collaboration with startups. She also explores explainability and validation frameworks for emerging technologies like large language models.

Anne’s recent publications span

• Predictive modeling for hip fracture mortality
• Frailty assessment in COVID-19
• Workflow integration of AI in ICU
• Comorbidity index limitations
• Class imbalance in ML models
• Shortness of breath triage systems

She is affiliated with the Julius Center at UMC Utrecht and previously conducted PhD research at Leiden UMC’s CAIRELab, combining a master’s in econometrics with clinical AI applications.