Health informatics is information engineering applied to healthcare. It manages the use of patient healthcare information and is a vast multidisciplinary field that spans information science, computer science, social science, behavioural science, management science, and others. It deals with the resources, devices, and methods required to optimise the acquisition, storage, retrieval, and use of information in medicine. In current medicine, data play critical roles in all stages of decision-making.
Processing and utilisation of this information to improve healthcare outcomes is the main goal of the Healthcare Informatics Research Group (HIGS). HIGS conducts multidisciplinary research at the cross-section of Artificial Intelligence, computer-based simulation, virtual and augmented reality, human-computer interaction, and robotics.
We concentrate on two main areas:
– we develop new diagnostic and therapeutic processes based on patient data to extract insights that can be used to improve patient care and prevention.
– we work on a new generation of medical communication and the incorporation of artificial intelligence (AI) in existing and new medical workflows.
Topics covered in this talk:
- Introduction, motivation, overview (Przemyslaw Korzeniowski)
- Applications of Artificial Intelligence in Medicine for Clinical Decision Support
- Noninvasive diagnosis of Pulmonary Hypertension (Michał Grzeszczyk)
- Fetoscopic field-of-view expansion for Twin-to-Twin Transfusion Syndrome (TTTS) treatment (Joanna Kaleta)
- Application of biclustering in the analysis of biological and medical data (Paweł Renc)
- Fetal birth weight prediction and biometry (Szymon Płotka)
- Orthodontic Treatment Planning (Tomasz Szczepański)
- Haptically-enhanced VR/AR for Improved Information Capture and Exchange in Medical/Social Environments (Jakub Chrobociński)
- Remote Examination Room (Przemysław Korzeniowski)
- Assistive Collaborative Robots for Mobility Impaired Patients (Amanuel Ergogo)
- Autonomous Ultrasound Examinations (Karol Pustelnik)
- Virtual Reality Simulations (not-only) for Surgical Training (Korzeniowski)
- Improving Real-Time Simulation with Deep Learning (Jan Kwapisz)
- Differentiable Simulation (Michał Naskręt)
- Autonomous Surgical Robots (Sabina Kamińska)
- Trust towards AI systems (Natalia Lipp)
- Science Communication (Przemysław Korzeniowski)
- Summary (Przemysław Korzeniowski)
