About
Paula Petrone is a UCD-affiliated researcher and biomedical data scientist specializing in artificial intelligence applications for healthcare. Her work bridges physics, machine learning, and biomedical research, focusing on synthetic data generation, early disease detection, and non-invasive imaging technologies.
- Collaborated with Newborn Solutions to develop an AI-powered ultrasound device for detecting infant meningitis in low-resource regions
- Developed machine learning models to identify preclinical Alzheimer's disease signatures via brain imaging
- Advocates for expanded access to patient data while balancing confidentiality concerns
Current research emphasizes synthetic data as a solution to data scarcity in clinical AI development, and challenges in algorithm generalization across diverse populations. She highlights the importance of interdisciplinary approaches in biomedical data science.
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