As it relates to biomedicine, the AI community is increasingly toeing the "snake oil" line.
Yes, machine learning/AI is powerful, but pie in the sky predictions such as the "end of disease" probably hurt more than help in the long run.
Yes, machine learning/AI is powerful, but pie in the sky predictions such as the "end of disease" probably hurt more than help in the long run.
It would be nice to see discussion of this in the article, but it focuses instead on the limitations of AI.
Testing these happens long before it ever goes to serious trials. Humans are very limited in how many results they can review, but if you can throw them to an AI and have it flag anything promising, then you've overcome a huge bottleneck.
This isn't magic or snake oil, and as the data often looks like microscope slides or tables of figures, it's well within the capabilities of current AI models.
Disease etiology spans both infectious and non-infectious. Infectious diseases are generally cured with antibacterial, antivirals, vaccines (what you call compounds).
Non-infectious (genetic, degenerative, metabolic, autoimmune) diseases typically involve therapies beyond “applying a compound”. We’ve seen breakthroughs like surgery (eg removing an appendix or a tumor). Gene therapies such as onasemnogene abeparvovec cures spinal muscular atrophy in infants. Certain leukemias or autoimmune diseases are cured via stem-cell transplants.