Portal & DrugKota
DrugKota
Hey, I’ve been curious about whether we could use machine learning to parse ancient herbal manuscripts and uncover new bioactive compounds—blending old wisdom with modern tech. What do you think?
Portal
Sounds like a neat fusion of old and new, and the tech can definitely lift a lot of those dusty pages—OCR to digitize, NLP to parse the text, then ML to flag patterns that match known bioactives. The trick is getting enough high‑quality scans and reliable annotations; once that’s in place, the models can start sniffing for hidden gems. Give it a shot—you might just resurrect some forgotten cures with a line of code.
DrugKota
That sounds like a real adventure—digging through the old scrolls with a computer’s eye and hoping it can pick up the subtle clues nature left behind. I can see the challenge of getting clear scans and trustworthy labels, but if we get that right, the patterns the machine spots might point us to remedies we’d otherwise miss. Let’s start small, maybe pick one well‑documented herb, digitize a few pages, and see what the algorithms can learn. It could be the first step toward blending centuries of knowledge with today’s tools.
Portal
That’s the vibe I like—tapping into a hidden archive with a neural net as your magnifying glass. Pick a herb, get some clean scans, label a few key terms, and let the model start mapping the old recipes to modern chemistry. The first few runs will be our proof‑of‑concept, and if it clicks, you’ll be on a path to unearthing whole new pathways.
DrugKota
Sounds like a plan. Let’s start with something familiar—maybe willow bark, since we already know salicin is there. If we get a decent set of scans, label the key parts, and run a quick model, we’ll see if the algorithm can actually pull out the same chemistry. If it does, we’ve got a solid proof‑of‑concept to build on. I’m excited to see what hidden pathways it uncovers.