Can I trust my fake data -- A comprehensive quality assessment framework for synthetic tabular data in healthcare

no code implementations • 24 Jan 2024 • Vibeke Binz Vallevik, Aleksandar Babic, Serena Elizabeth Marshall, Severin Elvatun, Helga Brøgger, Sharmini Alagaratnam, Bjørn Edwin, Narasimha Raghavan Veeraragavan, Anne Kjersti Befring, Jan Franz Nygård

We present a conceptual framework for quality assurance of SD for AI applications in healthcare that aligns diverging taxonomies, expands on common quality dimensions to include the dimensions of Fairness and Carbon footprint, and proposes stages necessary to support real-life applications.

Fairness

Unpacking Human-AI Interaction in Safety-Critical Industries: A Systematic Literature Review

no code implementations • 5 Oct 2023 • Tita A. Bach, Jenny K. Kristiansen, Aleksandar Babic, Alon Jacovi

We divided our investigation into the following research areas: (1) terms used to describe HAII, (2) primary roles of AI-enabled systems, (3) factors that influence HAII, and (4) how HAII is measured.

Decision Making

Doppler Spectrum Classification with CNNs via Heatmap Location Encoding and a Multi-head Output Layer

no code implementations • 6 Nov 2019 • Andrew Gilbert, Marit Holden, Line Eikvil, Mariia Rakhmail, Aleksandar Babic, Svein Arne Aase, Eigil Samset, Kristin McLeod

We analyze example images that fall outside of our proposed classes to show our confidence metric can prevent many misclassifications.

Decision Making General Classification