Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-learning model for fetal growth scans using both retrospective and prospective data. We used a modified Progressive Concept Bottleneck Model with pre-established clinical concepts as explanations (feedback on image optimization and presence of anatomical landmarks) as well as segmentations (outlining anatomical landmarks).

Video-based robotic surgical action recognition and skills assessment on porcine models using deep learning.

Objectives: This study aimed to develop an automated skills assessment tool for surgical trainees using deep learning.

Background: Optimal surgical performance in robot-assisted surgery (RAS) is essential for ensuring good surgical outcomes. This requires effective training of new surgeons, which currently relies on supervision and skill assessment by experienced surgeons.

Work ability following breast cancer - the MyHealth randomized controlled trial.

Background And Purpose: We previously demonstrated positive effects on quality of life and mental health following breast cancer when comparing a nurse-led follow-up program without scheduled visits (MyHealth) to regular follow-up. This study aims to examine whether MyHealth also positively impacts self-reported work ability.

Patients/material And Methods: A total of 288 patients, potentially active on the labour market, were randomized to MyHealth or control follow-up after primary treatment for early-stage breast cancer (2017-2019).

Survey of attitudes in a Danish public towards reuse of health data.

Everyday clinical care generates vast amounts of digital data. A broad range of actors are interested in reusing these data for various purposes. Such reuse of health data could support medical research, healthcare planning, technological innovation, and lead to increased financial revenue.