54 citations · 97 across the 12 of their papers we have counts for
13 papers
Multi-Objective Constraint Inference using Inverse reinforcement learning
Syed Ihtesham Hussain Shah, Floris den Hengst, Aneta Lisowska +1
Constraint inference is widely considered essential to align reinforcement learning agents with safety boundaries and operational guidelines by observing expert demonstrations. How…
LEGO Co-builder: Exploring Fine-Grained Vision-Language Modeling for Multimodal LEGO Assembly Assistants
Haochen Huang, Yue Su, Xin Sun +11
Vision-language models (VLMs) are facing the challenges of understanding and following multimodal assembly instructions, particularly when fine-grained spatial reasoning and precis…
Defining Effective Engagement For Enhancing Cancer Patients' Well-being with Mobile Digital Behavior Change Interventions
Aneta Lisowska, Szymon Wilk, Laura Locati +6
Digital Behavior Change Interventions (DBCIs) are supporting development of new health behaviors. Evaluating their effectiveness is crucial for their improvement and understanding…
Decoding Emotional Valence from Wearables: Can Our Data Reveal Our True Feelings?
Michal K. Grzeszczyk, Anna Lisowska, Arkadiusz Sitek +1
Automatic detection and tracking of emotional states has the potential for helping individuals with various mental health conditions. While previous studies have captured physiolog…
Personalising Digital Health Behaviour Change Interventions using Machine Learning and Domain Knowledge
Aneta Lisowska, Szymon Wilk, Mor Peleg
We are developing a virtual coaching system that helps patients adhere to behavior change interventions (BCI). Our proposed system predicts whether a patient will perform the targe…
Can gamification reduce the burden of self-reporting in mHealth applications? A feasibility study using machine learning from smartwatch data to estimate cognitive load
Michal K. Grzeszczyk, Paulina Adamczyk, Sylwia Marek +8
The effectiveness of digital treatments can be measured by requiring patients to self-report their state through applications, however, it can be overwhelming and causes disengagem…
Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings
Sophia Bano, Alessandro Casella, Francisco Vasconcelos +28
Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomos…
Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements
Szymon Płotka, Adam Klasa, Aneta Lisowska +4
Objective. This work investigates the use of deep convolutional neural networks (CNN) to automatically perform measurements of fetal body parts, including head circumference, bipar…
What do you need to consider when designing mobile health intervention?
Aneta Lisowska, Szymon Wilk, Mor Peleg
Designing theory-driven digital health interventions is a challenging task that needs support. We created a guide for the incomers in the field on how to design digital health inte…
CXR-FL: Deep Learning-Based Chest X-ray Image Analysis Using Federated Learning
Filip Ślazyk, Przemysław Jabłecki, Aneta Lisowska +2
Federated learning enables building a shared model from multicentre data while storing the training data locally for privacy. In this paper, we present an evaluation (called CXR-FL…
Continual Class Incremental Learning for CT Thoracic Segmentation
Abdelrahman Elskhawy, Aneta Lisowska, Matthias Keicher +3
Deep learning organ segmentation approaches require large amounts of annotated training data, which is limited in supply due to reasons of confidentiality and the time required for…
Paying Per-label Attention for Multi-label Extraction from Radiology Reports
Patrick Schrempf, Hannah Watson, Shadia Mikhael +6
Training medical image analysis models requires large amounts of expertly annotated data which is time-consuming and expensive to obtain. Images are often accompanied by free-text…
Teacher-Student chain for efficient semi-supervised histology image classification
Shayne Shaw, Maciej Pajak, Aneta Lisowska +2
Deep learning shows great potential for the domain of digital pathology. An automated digital pathology system could serve as a second reader, perform initial triage in large scree…