Medical Image Analysis and Machine Learning
My research centers around the development of machine learning solutions for health data science and precision medicine problems with a focus on machine learning-based medical image analysis. I am specifically interested in developing and advancing machine learning methods that accurately model the complex dynamics and variations of normal or pathological processes in the human body by integrating and combining diverse, large-scale medical data (e.g., images, clinical data, text reports). These models can then serve as clinical computer-aided diagnosis support tools or as tools for systematic data exploration in research scenarios. While the sensitivity and specificity of the models is of paramount importance in healthcare, my work also explicitly focuses on the explainability and interpretability of their decisions to enhance acceptability and trust by clinicians and patients. Finally, I am also interested in developing methods that achieve good results even if trained with limited data.