320 citations · 398 across the 22 of their papers we have counts for
5 papers · 1 filter
Open-source framework for detecting bias and overfitting for large pathology images
Anders Sildnes, Nikita Shvetsov, Masoud Tafavvoghi +5
Even foundational models that are trained on datasets with billions of data samples may develop shortcuts that lead to overfitting and bias. Shortcuts are non-relevant patterns in…
Coding historical causes of death data with Large Language Models
Bjørn Pedersen, Maisha Islam, Doris Tove Kristoffersen +4
This paper investigates the feasibility of using pre-trained generative Large Language Models (LLMs) to automate the assignment of ICD-10 codes to historical causes of death. Due t…
From research to clinic: Accelerating the translation of clinical decision support systems by making synthetic data interoperable
Pavitra Chauhan, Mohsen Gamal Saad Askar, Kristian Svendsen +4
The translation of clinical decision support system (CDSS) tools from research settings into the clinic is often non-existent, partly because the focus tends to be on training mach…
More efficient manual review of automatically transcribed tabular data
Bjørn-Richard Pedersen, Rigmor Katrine Johansen, Einar Holsbø +2
Machine learning methods have proven useful in transcribing historical data. However, results from even highly accurate methods require manual verification and correction. Such man…
Lessons learned developing and using a machine learning model to automatically transcribe 2.3 million handwritten occupation codes
Bjørn-Richard Pedersen, Einar Holsbø, Trygve Andersen +4
Machine learning approaches achieve high accuracy for text recognition and are therefore increasingly used for the transcription of handwritten historical sources. However, using m…