Discover and read the best of Twitter Threads about #spiritAI
Most recents (3)
*ANNOUNCEMENT*
(This time with correct links!)
On Feb 17th we’ll be releasing a new short course @Moorfields @StudyVisionUCL @UCLeye
“An introduction to AI for clinicians”
We're excited and proud to tell you all about it…
#OnDemand #Virtual #AI
checkout.moorfields.nhs.uk/product?catalo…
(This time with correct links!)
On Feb 17th we’ll be releasing a new short course @Moorfields @StudyVisionUCL @UCLeye
“An introduction to AI for clinicians”
We're excited and proud to tell you all about it…
#OnDemand #Virtual #AI
checkout.moorfields.nhs.uk/product?catalo…
Why are we doing this?!
Over the last 5+ years @MoorfieldsBRC we’ve learned that developing clinical AI is much more than coding.
In fact, it’s a broad spectrum...
#FromIdeatoAlgorithm
#FromCodeToClinic
Over the last 5+ years @MoorfieldsBRC we’ve learned that developing clinical AI is much more than coding.
In fact, it’s a broad spectrum...
#FromIdeatoAlgorithm
#FromCodeToClinic
@Moorfields we’ve been working on cutting-edge clinical AI with world-leading industry collaborators
@DeepMind @GoogleHealth @GoogleAI @googlecloud
#ReinventingTheEyeExam
@DeepMind @GoogleHealth @GoogleAI @googlecloud
#ReinventingTheEyeExam
1/NEW: Today the SPIRIT-AI and CONSORT-AI Working Group have published the first reporting guidelines for clinical trials evaluating AI interventions in @NatureMedicine @LancetDigitalH @bmj_latest
2/Papers here:
SPIRIT-AI nature.com/articles/s4159…; doi.org/10.1016/S2589-…; bmj.com/content/370/bm…
CONSORT-AI nature.com/articles/s4159…; doi.org/10.1016/S2589-…; bmj.com/content/370/bm…
SPIRIT-AI nature.com/articles/s4159…; doi.org/10.1016/S2589-…; bmj.com/content/370/bm…
CONSORT-AI nature.com/articles/s4159…; doi.org/10.1016/S2589-…; bmj.com/content/370/bm…
3/We need robust evaluations of *effectiveness* for AI interventions. As we move towards RCTs, #spiritAI and #consortAI will be crucial to ensuring robust, quality evidence.
Having reviewed a bunch of radiology papers lately with the same flaws - some #ML but most not - here are my top 10 tips! #AcademicChatter #radiology #AI
1/ Start with what is already known, where is the gap in knowledge and why it's important. Some papers are doomed from the start because there is no clear impact of the work. Remember the reviewer may not be super-specialised in your research niche.
2/ I need to understand the experimental design quickly, so a flowchart is really helpful. Put yourself in the shoes of a first-time reader. If the design is easy to follow then everything else fits into place.
