I'm a PhD candidate in Cancer Sciences with a focus on developing a risk prediction tool for fractures after radiotherapy. My work lies at the intersection of physics, data science and healthcare.
🔬 Research Focus:
I am currently pursuing a PhD in Cancer Sciences, where my primary research goal is to create a predictive model for identifying patients at risk of fractures after radiotherapy. By leveraging clinical data, machine learning, and advanced analytics, I aim to provide insights for personalised patient care.
💡 Previous Experience:
- Research Assistant: I developed a novel approach for spatial dose analysis and genomic research, enabling a more detailed understanding of the relationship between radiotherapy dose distributions and genetic factors influencing patient outcomes.
- CERN (LHCB): During my internship at CERN, I worked on the LHCB experiment, analysing vast datasets calculate matter-antimatter asymmetries. This experience honed my skills in managing and interpreting large-scale, complex datasets.
- Sustainability and Innovation Projects: I have also contributed to projects focused on sustainability, such as ZEROPLUS using innovative solutions to tackle real-world problems. These experiences helped me understand how data-driven approaches can address global challenges across industries.
- Programming & Tools: Python, MATLAB, C++, R
- Data Science: Image-based data mining, Statistical analysis, Data visualisation
- Software Development: HTML, CSS, JavaScript, React, Django, SQL, Git
- Website: https://artemis-bouzaki.github.io/
