Publications by authors named "A HAUG"

Article Synopsis
  • Radical prostatectomy (RP) is a standard treatment for localized prostate cancer, but accurately detecting extraprostatic extension (EPE) before surgery is difficult, which can lead to suboptimal treatments.
  • This study explores using explainable machine learning to improve EPE detection by analyzing data from newly diagnosed prostate cancer patients who underwent PET/MRI imaging and subsequent surgery.
  • The results showed machine learning models outperformed traditional imaging methods in predicting EPE, which could lead to better clinical decision-making and improved patient outcomes.
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Article Synopsis
  • Patient-derived tumour organoids (PDOs) were combined with the chorioallantoic membrane (CAM) of chicken eggs to create a vascularized model, aiming to study liver metastasis from colorectal cancer (CRC).
  • The resulting xenografts showed high viability and vascularization, closely resembling the original patient's liver metastasis in both morphology and protein expression (CXCR4).
  • Although the study observed [Ga]Ga-Pentixafor uptake in the CAM-PDXs, the results indicated no significant differences compared to initial PDOs, highlighting the potential for this model in translational cancer research.
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Article Synopsis
  • This study looked at how to better grade prostate cancer using a new machine learning model that combines different types of medical data.
  • They analyzed information from 146 patients who had specific imaging tests before surgery and created five different models to see which worked best.
  • The best model, called the random forest model, outperformed the usual grading method, helping doctors find patients at higher risk for more personalized treatment.
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In the fractional quantum Hall effect, quasiparticles are collective excitations that have a fractional charge and show fractional statistics as they interchange positions. While the fractional charge affects semi-classical characteristics such as shot noise and charging energies, fractional statistics is most notable through quantum interference. Here we study fractional statistics in a bilayer graphene Fabry-Pérot interferometer.

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Background And Purpose: In Norway, comprehensive molecular tumour profiling is implemented as part of the public healthcare system. A substantial number of tumours harbour potentially targetable molecular alterations. Therapy outcomes may improve if targeted treatments are matched with actionable genomic alterations.

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