Future Horizons in Healthcare (AI in med) Flashcards
How can AI and large-scale cell atlases change our understanding of diseases like cancer, autoimmune disorders, and neurodegenerative conditions?
They help analyse massive data and find patterns in diseases, lead to better understanding and new treatment targets for cancer, autoimmune, and neurodegenerative diseases.
Challenges: It’s hard to turn this knowledge into treatments because of the complexity of biology, high costs, and ethical concerns around data privacy.
How could AI and in silico experiments change traditional biological research over the next 20 years?
AI can simulate experiments on computers (in silico), speeding up research, reducing the need for animal testing, and making drug discovery faster and cheaper.
Implications:
This shift raises ethical concerns, like data ownership and accuracy of simulations. We also need to ensure that computer models match real-life biology.
How might CELLxGENE and Tabula Sapiens impact global healthcare equity?
These open-access resources can advance personalised medicine by helping develop treatments tailored to individuals.
Steps for equity:
To ensure global access, there must be investment in education, infrastructure, and making treatments affordable in low-income regions.
