About the project
Objective
The objective of the project is to identify and characterize clusters of patients and their dynamics over time such that the patients respond optimally to medical caregivers’ interventions and medications. In collaboration with Karolinska Institute and Region Stockholm, we will focus on dementia patients for personalized treatments and develop an advanced AI-based predictive analysis method to help medical caregivers for their decisions.
Background
It has been observed that patients suffering of a same disease can respond differently to the same medication. This can slow down medical treatments and even worsen the disease prognoses. How can we then make medical treatments personalized to improve the disease progression of patients over time?
Dementia patients have multiple follow-ups over time, generating longitudinal data. In a large patient pool, there can be several clusters, some representing patients who are more receptive and doing better with interventions and medications, and other clusters representing a more limited scope. Individual patients may also change clusters over time. Predictive analysis is required to make treatment decisions based on a patient’s personalized profile and the patient’s similarity across other patients over time. Modern sequence-based AI-methods are useful to make predictions on this type of data, and topological data analysis can give insights about characteristics and relations between patients by studying the shape of the data. These methods can help us find clusters of patients, characterize their disease progression and develop a decision care system for personalized treatments.
About the Digital Futures Postdoc Fellow
Belén García Pascual completed her PhD in biomathematics in October 2024 at the University of Bergen (Norway). She developed mathematical and computational models to explore questions in evolutionary and cell biology, with a focus on mitochondrial genes and evolutionary progression pathways of antimicrobial resistance. During the PhD, Belén did an industry internship at DNV in Oslo (Norway) researching how large language models can generate realistic synthetic data in healthcare. Before, she took her master in topology at the University of Bergen, and her bachelor in mathematics at Complutense University of Madrid (Spain).
Main supervisor
Martina Scolamiero
Co-supervisor
Saikat Chatterjee
