Preterm Birth Prediction
Preterm Birth Prediction based on fetal transvaginal ultrasound videos using Deep Learning methods.
Multidisciplinary research at the interface of computing, information technology, behavioral science, human-computer interaction, and AI, focused on healthcare workflows, patient data management, data visualization, interaction and communication applied to on-site and remote medicine.
Manages the use of patient healthcare information and deals with the resources, devices, and methods required to optimize acquisition, storage, retrieval, and use of information in medicine. This team concentrates on a new generation of approaches to medical communication and incorporation of output of computational methods (data science, in-silico methods) in medical workflows. New models of information exchange between existing decision agents (patients, their families, doctors, care teams) are considered and investigated. Intuitive interfaces for improved understanding of health-related data and AI insights will be an important part of this effort.
This team will, among others, investigate new computer interfaces for enhanced perception of multi-modality, multi-source medical data, including 3D virtual interactive environments. Using such environments for advanced remote interactive communication without the need for physical co-presence will improve today’s telemedicine, also in the context of pandemic threats. For smaller medical centres, and rural area care, these solutions will allow for remote virtual interaction between patients and specialists, and advanced, data-driven specialist consultations. The Health Informatics team will also investigate optimal decision-making when heterogeneous information sources – machine recommendations, expert human knowledge, and patient preferences – are combined during the health-related decision-making process.