Publications by authors named "F M M A van der Heijden"

Objectives: We explored whether gender differences in burnout and work engagement characteristics among residents changed after the representation of female physicians has surpassed the 30% threshold of critical mass between 2005 and 2015, as well as if these gender differences are influenced by working in a surgical versus a non-surgical specialty.

Methods: This study used data of two questionnaire surveys on the well-being of Dutch residents, collected in 2005 ( = 2115) and 2015 ( = 1231). Burnout was measured with the validated Dutch translation of the Maslach Burnout Inventory, covering the characteristics emotional exhaustion, depersonalisation and personal accomplishment.

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Article Synopsis
  • Abdominal Normothermic Regional Perfusion (aNRP) is a technique used before organ donation that helps evaluate organ quality during controlled donation after circulatory death (cDCD).
  • A study compared pancreatic islet isolation outcomes from aNRP donors to those from cDCD and Donation after Brain Death (DBD) donors, finding that aNRP yielded significantly more islets.
  • The study showed that islets from aNRP donors demonstrated good functionality, suggesting that this technique could enhance the availability and quality of pancreases for islet transplantation.
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Purpose: In an effort to reduce waitlist mortality, extended criteria donor organs, including those from donation after circulatory death (DCD), are being used with increasing frequency. These donors carry an increased risk for postoperative complications, and balancing donor-recipient risks is currently based on generalized nomograms. Abdominal normothermic regional perfusion (aNRP) enables individual evaluation of DCD organs, but a gold standard to determine suitability for transplantation is lacking.

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Objectives: We sought to investigate if artificial medical images can blend with original ones and whether they adhere to the variable anatomical constraints provided.

Methods: Artificial images were generated with a generative model trained on publicly available standard and low-dose chest CT images (805 scans; 39,803 2D images), of which 17% contained evidence of pathological formations (lung nodules). The test set (90 scans; 5121 2D images) was used to assess if artificial images (512 × 512 primary and control image sets) blended in with original images, using both quantitative metrics and expert opinion.

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Purpose: Pleural plaques (PPs) are morphologic manifestations of long-term asbestos exposure. The relationship between PP and lung function is not well understood, whereas the time-consuming nature of PP delineation to obtain volume impedes research. To automate the laborious task of delineation, we aimed to develop automatic artificial intelligence (AI)-driven segmentation of PP.

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