Publications by authors named "C B Alme"
Machine learning approaches for predicting craniofacial anomalies with graph neural networks.
Comput Biol Chem
December 2024
Article Synopsis
- The study investigates how machine learning, particularly traditional methods and graph neural networks (GNNs), can be used to predict diseases by analyzing complex protein-protein interactions (PPIs).
- PPIs are challenging to analyze due to their complexity and variability, making traditional computational methods less effective.
- Machine learning and GNNs are shown to be more effective in detecting complex patterns and achieving better accuracy in predictions across networks of different sizes, with an emphasis on the importance of network features.
Purpose: GATA2 deficiency is a rare primary immunodeficiency that has become increasingly recognized due to improved molecular diagnostics and clinical awareness. The only cure for GATA2 deficiency is allogeneic hematopoietic stem cell transplantation (allo-HSCT). The inconsistency of genotype-phenotype correlations makes the decision regarding "who and when" to transplant challenging.
View Article and Find Full Text PDFBackground And Objectives: The status of red blood cell alloimmunization in patients with constitutional anemias including hemoglobinopathies is not known in Norway. The study objective was to investigate the impact of a strategy based on phenotype-matching for C, c, E, e, K, Jka, Jkb, Fya, Fyb, S and s on alloimmunization.
Materials And Methods: We reviewed transfusions of 40 patients retrospectively using the computerized blood bank management system and medical records; including diagnosis, age at start of transfusion therapy, gender, number and age of packed red blood cell units transfused, follow-up time, phenotypes of the donors and patients, antigen-negative patients exposed to antigen-positive packed red blood cell units, transfusion reactions and alloantibody specificities.