Sonja Aits
- Cell Death, Lysosomes and Artificial Intelligence
- Neuroinflammation
- Division of Microbiology, Immunology and Glycobiology - MIG
- BioCARE: Biomarkers in Cancer Medicine improving Health Care, Education and Innovation
- MultiPark: Multidisciplinary research on neurodegenerative diseases
- eSSENCE: The e-Science Collaboration
- LUCC: Lund University Cancer Centre
- EpiHealth: Epidemiology for Health
- LTH Profile Area: AI and Digitalization
- LU Profile Area: Natural and Artificial Cognition
- LU Profile Area: Nature-based future solutions
- LTH Profile Area: Engineering Health
- LU Profile Area: Proactive Ageing
- BECC: Biodiversity and Ecosystem services in a Changing Climate
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- 2025
-
Mark
An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlines
- Contribution to journal › Article
-
Mark
A Deep Learning Pipeline for Genome-Wide Imaging Screen Uncovering Cell Death Regulators
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
-
Mark
Mapping disease-environment connections reported in scientific literature at scale with EasyNER
(2025) EurIPS 2025
- Contribution to conference › Paper, not in proceeding
-
Mark
Artificial intelligence approaches for mapping the nexus of biodiversity, climate change and human society
(2025) Swedish Biodiversity Symposium
- Contribution to conference › Abstract
- 2024
-
Mark
The Cell Death Census 2024
(2024)
- Working paper/Preprint › Preprint in preprint archive
-
Mark
An annotated high-content fluorescence microscopy dataset with 2 EGFP-Galectin-3-stained cells and manually labelled outlines
(2024)
- Working paper/Preprint › Preprint in preprint archive
-
Mark
AI regulation — Struggling to Keep Up
(2024)
- Other contribution › Web publication
-
Mark
Get the most out of ChatGPT and similar chatbots - a guide for scientists and professionals
(2024)
- Other contribution › Web publication
-
Mark
BioBERT_HUNER_v2 models
(2024)
- Non-textual form › Software
-
Mark
EasyNER: A Customizable and Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text [Software]
(2024)
- Non-textual form › Software
