Our first deep dive on AI in Healthcare is finally complete.
Read the full article for details on studies, resources, and interviews.
https://lnkd.in/eZBr48dt
Top Highlights
🩺 Precision medicine promises improved health outcomes but requires more data, diagnostics, and long-term monitoring than current healthcare standards.
🚀New tools utilizing #AI are able to advance personalized medicine by making it easier and more accurate to interpret the vast troves of data needed for personalization.
💊 Oncology and #BioPharma are two sectors where AI for precision care are the furthest along the technology adoption curve.
❓Innovators who are pioneering applications of AI cite that access to quality clinical data is one of the top challenges to training models and achieving highly accurate AI enabled tools. Clinical data is fragmented and hard to access.
📉Advancements in AI technology are reducing the cost and effort required to build new AI based solutions. Notably: pre-trained models, improvements in hardware and partnership programs such as the Mayo Clinic Platform Accelerate that grant #startups access to data for training models.
Thank you to our team who spent hours in outreach, interviews, synthesis, and editing: Morgan Swigert Jessica Malosh and Dmitry Tyshlek
Thank you Lars Wiersholm at FibriCheck and Nikhil Joshi at Cellular Vehicles for your inputs - we were grateful to be able to use your technologies in the case studies. Thank you Nicole Black, PhD for the connections!