Perfect example of using #AIForGood 🤝
What makes the new AI tool better than existing models? 🤖🧠🧐
“Most current AI models used for drug discovery are trained on a single disease or a handful of conditions. Rather than focusing on specific diseases, the new tool was trained in a manner that enables it to use existing data to make new predictions. It does so by identifying shared features across multiple diseases, such as shared genomic aberrations.
For example, the AI model pinpoints shared disease mechanisms based on common genomic underpinnings, which allows it to extrapolate from a well-understood disease with known treatments to a poorly understood one with no treatments.
This capacity, the research team said, brings the AI tool closer to the type of reasoning a human clinician might use to generate novel ideas if they had access to all the preexisting knowledge and raw data that the AI model does but that the human brain cannot possibly access or store.
The tool was trained on vast amounts of data, including DNA information, cell signaling, levels of gene activity, clinical notes, and more. The researchers tested and refined the model by asking it to perform various tasks. Finally, the tool's performance was validated on 1.2 million patient records and asked to…”