Self-supervised Learning for Tumor Microenvironment Analysis: Addressing Label Scarcity in Multiplexed Immunofluorescence Imaging with Novel Feature Extraction Techniques

Enriching Machine Learning Model Metadata: Collecting performance metadata through automatic evaluation

Host- Microbiome Omics Integration for Cancer Analysis and Diagnostics: Investigating the added value of integrating microbial and host omics information for cancer diagnostics using prediction models

Finding values in green hydrogen using topic modelling: Building a framework for explorative modelling

Identification of Neolithic Circular Enclosures through Aerial Imagery

Algal Bloom Forecasting using Remote Sensing: Discovering the most predictive data modalities for Algal Bloom Forecasting

Modeling C-band radar observables over sugarbeet fields using machine learning

Data-driven assisted model specification for complex choice experiments data: Association rules learning and random forests for Participatory Value Evaluation experiments

Evaluating classifiers in SE research: the ECSER pipeline and two replication studies

Predicting the influence of geometric imperfections on the mechanical response of 2D and 3D periodic trusses

Digitization of chemical process flow diagrams using deep convolutional neural networks

SoK: Explainable Machine Learning for Computer Security Applications

What factors contribute to the acceptance of artificial intelligence? A systematic review

Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges

Data-driven corrosion inhibition efficiency prediction model incorporating 2D–3D molecular graphs and inhibitor concentration

Generating quality datasets for real-time security assessment: Balancing historically relevant and rare feasible operating conditions

Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings

Development of a hydrate risk assessment tool based on machine learning for CO₂ storage in depleted gas reservoirs

Machine learning approaches exploring the optimal number of driver profiles based on naturalistic driving data

Physics-based modelling and data-driven optimisation of a latent heat thermal energy storage system with corrugated fins