AI Tool Identifies Aggressive Cancer Cells
A new AI tool developed by Jun Ding identifies the most aggressive cancer cells and predicts patient outcomes.
View news items and posts from some of our respiratory research publications. For a complete publication list, please go here: https://meakinsmcgill.com/publications/
A new AI tool developed by Jun Ding identifies the most aggressive cancer cells and predicts patient outcomes.
New study by Faiz Ahmad Khan reveals how Inuit communities in Nunavik experience tuberculosis care and calls for more culturally safe, community-led approaches to improve outcomes.
A new injectable gel boosts stem cell survival and could advance regenerative treatments.
Dao Nguyen co-develop a 36-minute diagnostic test to rapidly identify bacteria and antibiotic susceptibility.
Study by Ben Smith introduces height-GaP, a simple measure linking early-life growth adversity to adult mortality risk, revealing how childhood conditions shape lifelong health.
A major eLife Focus Issue highlights 10+ years of trained immunity research, featuring key contributions from Meakins scientists
Study by Jonathon Campbell shows that scaling up existing TB screening and preventive treatments will save lives and costs
Nicole Li-Jessen develops biomaterials for vocal tissue and muscle reconstruction and developed an injectable hydrogel that could restore damaged vocal cords
Jun Ding and team have developed DOLPHIN, an AI tool that goes beyond gene-level analysis to detect overlooked disease markers
Dennis Jensen developed the first wearable system to can predict early inflammation from infections