Sessions
The conference at Vitalis 2023 consists of several tracks with panel discussions, keynote presentations and studio talks. Most of the content will also be available online via live broadcasts and recorded lectures, available on demand.
Search the programme and customise your agenda!
You can filter by topic, seminar type, target audience or time. There are also a number of thematic tracks in the programme.
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Track
Nationally shared medication lists – describing systems in the Nordic countries
Tora Hammar, Trine Bergmo, Unn Sollid Manskow, Anette Vik Jøsendal
Tuesday May 23, 2023 14:00 - 14:15 G1
MIE: Health information systems, English, On site only, Presentation, Advanced
Interdisciplinary Human-Centered AI for Hospital Readmission Prediction of Heart Failure Patients
Amira Soliman, Marcus Petersson, Jens Nygren, Lina Lundgren, Ebba Fogelberg, Petra PetraDryselius, Monika Nair, Kobra Etminani
Tuesday May 23, 2023 14:00 - 14:15 G2
MIE: Decision support, English, On site only, Presentation, Advanced
Cross-registry benchmarking of data quality: Lessons learned
Jürgen Stausberg
Tuesday May 23, 2023 14:00 - 14:15 G3
MIE: Health information systems, English, On site only, Presentation, Advanced
Low Valence Low Arousal stimuli: An Effective Candidate for EEG-based Biometrics Authentication System
Jahanvi Jeswani, Praveen Kumar Govarthan, Tikaram
Tuesday May 23, 2023 14:15 - 14:30 G1
MIE: Health information systems, English, Pre-recorded + On-site, Presentation, Tools for implementation, Introductory, Researchers, Students, Healthcare professionals, Innovation/research
Electroencephalography (EEG) has recently gained popularity in user authentication systems since it is unique and less impacted by fraudulent interceptions. Although EEG is known to be sensitive to emotions, understanding the stability of brain responses to EEG-based authentication systems is challenging. In this study, we compared the effect of different emotion stimuli for the application in the EEG-based biometrics system (EBS). Initially, we pre-processed audio-visual evoked EEG potentials from the ‘A Database for Emotion Analysis using Physiological Signals’ (DEAP) dataset. A total of 21 time-domain and 33 frequency-domain features were extracted from the considered EEG signals in response to Low valence Low arousal (LVLA) and High valence low arousal (HVLA) stimuli. These features were fed as input to an XGBoost classifier to evaluate the performance and identify the significant features. The model performance was validated using leave-one-out cross-validation. The pipeline achieved high performance with multiclass accuracy of 80.97% and a binary-class accuracy of 99.41% with LVLA stimuli. In addition, it also achieved recall, precision and F-measure scores of 80.97%, 81.58% and 80.95%, respectively. For both the cases of LVLA and LVHA, skewness was the stand-out feature. We conclude that boring stimuli (negative experience) that fall under the LVLA category can elicit a more unique neuronal response than its counterpart the LVHA (positive experience). Thus, the proposed pipeline involving LVLA stimuli could be a potential authentication technique in security applications.
Blood Vessel Segmentation using U-Net for Glaucoma Diagnosis with Limited Data
Lukas Schießer
Tuesday May 23, 2023 14:15 - 14:30 G2
MIE: Decision support, English, On site only, Presentation, Advanced
Why are Data Missing in Clinical Data Warehouses? A Simulation Study of How Data are Processed (and can be lost)
Sonia Priou
Tuesday May 23, 2023 14:15 - 14:30 G3
MIE: Health information systems, English, On site only, Presentation, Advanced
Challenges with medication management and the National Medication List in Sweden: an interview study from a human, organizational, and technology perspective
Tora Hammar, Mikael Hoffmann, Lina Nilsson
Tuesday May 23, 2023 14:30 - 14:45 G1
MIE: Health information systems, English, On site only, Presentation, Advanced
PDSS: A Pharmacological Decision Support System for Diabetics patients with COVID-19
Isabel Amaya Rodríguez
Tuesday May 23, 2023 14:30 - 14:45 G2
MIE: Decision support, English, On site only, Presentation, Advanced
DeepTSE: A time-sensitive Deep Embedding of ICU Data for Patient Modeling and Missing Data Imputation
Michael Fujarski
Tuesday May 23, 2023 14:30 - 14:45 G3
MIE: Health information systems, English, On site only, Presentation, Advanced
Timeline of and Expectations for the National Medication List in Sweden
Mikael Hoffmann
Tuesday May 23, 2023 14:45 - 15:00 G1
MIE: Health information systems, English, On site only, Presentation, Advanced
Patient Electronic Health Record as Temporal Graphs for Health Monitoring
Hugo LE BAHER
Tuesday May 23, 2023 14:45 - 15:00 G2
MIE: Decision support, English, On site only, Presentation, Advanced
Patient Registration Work of Medical Secretaries in the Era of Data-Driven Healthcare
Casper Knudsen
Tuesday May 23, 2023 14:45 - 15:00 G3
MIE: Health information systems, English, On site only, Presentation, Advanced
Identifying and Predicting Postoperative Infections Based on Readily Available Electronic Health Record data
Siri Van Der Meijden
Tuesday May 23, 2023 15:00 - 15:05 G1
MIE: Health information systems, English, On site only, Presentation, Advanced
Parallel Recurrent Convolutional Neural Network for Abnormal Heart Sound Classification
Ankica Babic, Arash Gharehbaghi, Arash Gharehbaghi
Tuesday May 23, 2023 15:00 - 15:15 G2
MIE: Decision support, English, On site only, Presentation, Advanced
Patients' Experiences of Unwanted Access to their Online Health Records
Annika Bärkås
Tuesday May 23, 2023 15:00 - 15:05 G3
MIE: Health information systems, English, On site only, Presentation, Advanced
Learning from Health Professionals: A User-Centred Approach to Design a Wound Monitoring Platform
Beatriz Félix, Ricardo Melo
Tuesday May 23, 2023 15:05 - 15:10 G1
MIE: Health information systems, English, On site only, Presentation, Advanced
Post hoc sample size estimation for deep learning architectures for ECG-classification
Lucas Bickmann
Tuesday May 23, 2023 15:45 - 16:00 G1
MIE: Health information systems, English, On site only, Presentation, Orientation, Advanced, Technicians/IT/Developers, Researchers, Students, Innovation/research
Traditional sample size estimation for sufficient model performance is not applicable for machine learning, especially in the field of electrocardiograms (ECGs). This presentation outlines a sample size estimation strategy for binary classification problems on ECGs. The post-hoc sample size estimations are based on a benchmark across different architectures and different classification targets. The results indicate trends for required sample sizes for given tasks and architectures, which can be used as orientation for future ECG studies or feasibility aspects.
Evidence of Digital Health Applications from a State-Regulated Repository for Reimbursable Health Applications in Germany
Ute von Jan, Dennis Lawin, Evgenii Pustozerov, Florian Dittrich, Urs-Vito Albrecht
Tuesday May 23, 2023 15:45 - 16:00 G2
MIE: Telehealth, English, On site only, Presentation, Advanced
Clinical decision support: Evaluating the development of a tool for nurses
Bente Christensen, Ann Kristin Rotegård
Tuesday May 23, 2023 15:45 - 16:00 G3
MIE: Decision support, English, On site only, Presentation, Advanced
International Perspectives on Ethical Principles Across the AI Lifecycle
Jean Louis Raisaro, Fabian Prasser, Bradley Malin, Laurie Novak
Tuesday May 23, 2023 15:45 - 17:15 G4
MIE: Societal aspects, English, On site only, Panel, Advanced