PhD Researcher Janine Zitianellis Presenting at the Applied AI Summit
Monarch Business School Switzerland is proud to announce that PhD candidate Janine Zitianellis will be presenting her research at the 2025 Applied AI Summit. Her work investigates the application of natural language processing (NLP) to map pre-screening responses from clinical trial participants to theoretical constructs from the Health Belief Model. This data is then integrated with an XGBoost classifier and survival-derived risk scoring to examine how machine learning can support behaviorally-informed, time-sensitive recruitment strategies. The research contributes to the advancement of applied AI in healthcare and behavioral analytics.
The Applied AI Summit attracts leading experts from academia, industry, and research institutions worldwide. Previous and current speakers include representatives from Google DeepMind, Stanford University, Microsoft Research, the Mayo Clinic, MIT, Amazon Web Services, and the National Institutes of Health. The summit is recognized as a key platform for the exchange of advanced research and real-world applications of generative AI, NLP, and machine learning technologies across critical domains. Ms. Zitianellis represents Monarch Business School Switzerland within this high-calibre group of contributors, reflecting the Monarch’s commitment to advancing applied research and demonstrating the academic rigor and real-world relevance of the doctoral work undertaken at Monarch.
About The Research
Janine Zitianellis’s research focuses on enhancing clinical trial recruitment through the integration of behavioral theory and machine learning. Drawing on the Health Belief Model (HBM), she developed a method to align unstructured patient pre-screening responses with constructs such as perceived barriers, susceptibility, and cues to action using large language models and Named Entity Recognition. These behavioral features were then incorporated into a predictive model combining XGBoost classification and survival-derived risk scoring. The model’s transparency was validated through SHAP analysis, which identified social vulnerability and perceived barriers as key drivers of patient progression. Her framework adheres to ethical guidelines such as GCP and the Declaration of Helsinki, and demonstrates how equity-informed AI approaches can improve trial design, reduce attrition, and inform scalable, real-time digital screening tools in healthcare.
This global, 3-day event dives deep into real-world applications of generative AI, large language models (LLMs), and advanced NLP across industries including healthcare, finance, legal, life sciences, and more. Now in its 6th year, the Applied Generative AI Summit features 30+ keynote presentations and expert-led sessions showcasing practical case studies, implementation strategies, and the latest breakthroughs in open-source models, tools, and frameworks. Discover how organizations are deploying LLMs at scale, navigating ethical and technical challenges, and unlocking real business value through applied AI.
About The Researcher
PhD Candidate Janine Zitianellis is a creative and passionate professional with a proven track record of delivering results. She advocates for the ethical use of data and analytics, supporting data-driven decision-making and aiming to provide business value through actionable insights. Janine possesses a broad range of skills and deep expertise in advanced analytics, machine learning, data mining methodologies, data quality, and visualisation. Her successful career spans several industries, including pharmaceuticals and biotechnology, banking, credit and collections, retail, and manufacturing. In addition to her enthusiasm for data science, Janine is deeply committed to giving back to her community. She actively supports multiple initiatives, including Friends of Care Animal Welfare, and serves as an ambassador for The Warrior Project—an organisation focused on combating gender-based violence. Janine holds a master’s degree in data analytics and operations management from Arden University and has completed a postgraduate programme in data science and business analytics at the McCombs School of Business at the University of Texas. Currently, she is pursuing a PhD at Monarch Business School in Switzerland.