If you have a dataset that could be valuable for biomedical research, here are a few key points to consider from our perspective as data integrators and users in research-centric biotech and pharma projects.
Read more...
data
shorts
We have recently deployed a biomedical LLM system that now helps with finding drugging opportunities for a novel modality. In this post, we share the technical stack we used.
Read more...
llm
arachne.ai
data
This post tries to explain, using an enormous simplification, the difference between two leading families of data models that are in use in modern data workflows, especially in the context of feeding ML/AI - relational and document/object representations.
Read more...
technical
data
arachne.ai
For the past several months, we have been finalising the first usable release of a system that we think would remedy some high-impact pain points we have seen in working with data in high-paced bio- and med-tech companies.
Read more...
arachne.ai
data
Health and clinical data is a central part of understanding the reality of dealing with diseases. The need for it only increases while the access-related challenges make it complicated to acquire. Thankfully due to a recent effort by HDRUK, more and more datasets can be shared.
Read more...
biokeanos
data
There is an unprecedented demand for biomedical data both for research and application, driven by the availability of large-scale processing technology and the resurgence of predictive modelling / AI. Given the vast amount of possible sources, how does one know which one they should be using?
Read more...
biokeanos
data