bioRxiv.
Using LLM Models and Explainable ML to Analyse Biomarkers at Single Cell Level for Improved Understanding of Diseases.
Frontiers in Nutrition.
Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach.
Nature Mental Health.
Plasma proteomics discovery of mental health risk biomarkers in adolescents.
Abzu identified which metabolites are present in early or late denning in bears.
Understanding how bears can hibernate without developing blood clots or muscle atrophy can help humans prepare for the future of space travel.
AIP Conference Proceedings.
Analysis of the relationship between fetal health prediction features with machine learning Feyn QLattice regression model.
Annals of Medicine.
Artificial intelligence for diagnosis of mild–moderate COVID-19 using haematological markers.
NASA GeneLab 2023 AWG Symposium: The year of open science.
Abzu’s Jonas Elsborg presents his research with NASA GeneLab: “Elucidating dermatological changes in spaceflight with explainable AI.”
Information Fusion.
Information fusion via symbolic regression: A tutorial in the context of human health.
The TOLAC project.
The TOLAC project brings data-driven insights to expectant parents at important stages of pregnancy to reduce the risk inherent in vaginal or caesarian delivery.
Abzu® selected partner for EU project Elegant North to create a new strategy for handling data on rare diseases.
To address the deficiency of treatments for rare diseases, the selected partners in project Elegant North will create a cross-border, rare disease data-sharing platform to foster cross-sector collaboration between researchers, companies, and healthcare systems.
