Fluorescence imaging is a valuable tool for biological analysis but is time-consuming and toxic to the cells. Using deep learning to virtually stain bright-field images is an active field of research that can alleviate these problems. Phil Harrison, a PhD student in the HASTE group, presented a poster at the Swedish Symposium on Deep Learning (SSDL) 2021 based on the HASTE team’s winning solution for the Adipocyte Cell Imaging Challenge. The poster presented our approach and results.
Many in the HASTE team visited the conference: Phenotypic Screening, High-Content Analysis and AI: Overcoming the Challenges that was held March 2-3rd at AstraZeneca, Gothenburg, Sweden.
Ola Spjuth shared the session AI and Machine Learning where Carolina Wählby (PI of HASTE) and Phil Harrison (PhD student in HASTE) gave presentations.
Discovering new drugs is becoming more costly. Lars Carlsson gave a presentation Machine Learning For Smarter Drug Discovery at RISE SICS Data Science & AI Day, Nov 28, 2017, where he gave some examples of how AstraZeneca is trying to improve the drug discovery phases through the use of machine learning.