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Medical Intelligence Society Summit 2021 - Shared screen with speaker view
Piyush Mathur
01:32
Aloha from Maui everyone!
Avneesh Khare
06:08
Break the silos!
Piyush Mathur
08:05
Perfect day with AI and live Maui backdrop! Thanks to all the organizers and participants for getting this together.
Piyush Mathur
08:54
https://informatics.bmj.com/content/bmjhci/27/1/e100183.full.pdf
Piyush Mathur
09:31
https://informatics.bmj.com/content/27/3/e100221
Avneesh Khare
09:34
Rising cost of healthcare is a big threat!
Piyush Mathur
09:38
The 2 papers I mentioned
Zaidon Al-Falahi
10:04
A question to the panel. Over the last 2-3 years we set out to create a cross-specialty data infrastructure to capture every data point possible from all our labs, specialties and Cerner. The purpose is to create a digital twin and make curated data available for AI research. COVID helped us get the ethics approval required, perhaps the most important milestone. The issue we're deliberating on now is the choice of technology and future proofing. I am very keen on open source everything and maximizing interoperability ad am pushing in that direction. Any wisdoms on how best to do that?
Piyush Mathur
11:00
Good question Zeidon.One word answer: Persistence!
Piyush Mathur
11:32
Trying different approaches and addressing each barrier.
Avneesh Khare
11:35
Is any centre presently using ‘silent implementation’ of AI solutions?
Piyush Mathur
12:54
Yes,many are Avneesh in trial mode or for validation.
Tim McLerran
16:01
Suppose you have an AI algorithm you want to implement in clinical workflows. What general infrastructural components must be in place to bring it to the bedside, and how can we systematically provide such infrastructure to both the ivory towers and to underserved populations?
Piyush Mathur
17:15
Great question Tim,I firmly believe there needs to be translational group which helps with implementation and is resourced adequately.Human computer interface expertise is very much needed there.
Piyush Mathur
17:37
Its one of the most underestimated problem of AI in healthcare.
Piyush Mathur
18:07
For the second part, we are not there yet…..
Ajay Perumbeti
18:34
For clinical AI, if AI is clinical decision support, and considered by FDA as a device if its not highly understandability, what is best practice to deploy. Do you use disclaimers liberally?
Avneesh Khare
20:32
Yes maybe that’s why I read some awesome academic papers but go back to facing similar bedside problems everyday. We need better implementation on ground.
Fatme Charafeddine
21:00
I always like the pacemaker analogy :)
Zaidon Al-Falahi
21:22
A biochemistry analyser is a blackbox too. We put a blood sample and it generates a set of numbers that we trust without questioning how it works. We just trust that it has been "calibrated"
Piyush Mathur
21:43
Validity is more important
Arlen Meyers
22:09
If it has been determined that it is a device, you should conmply with the appropriate standards
Tim McLerran
22:51
Thanks for the answer Piyush. It sounds like implementation will be very resource-intensive as long as we are all using different systems. You can’t just write a new algorithm and a new interface into the EHR system and push it out like an iPhone update if everyone is using different systems, right? So is the underlying problem that we are all running such different systems? Is there any way around that, or will we eventually have to converge on the same systems in order to democratize AI implementation?
Avneesh Khare
23:16
Great analogies 👍
Ajay Perumbeti
23:22
Doesn't the FDA care if its a black box though?
Fatme Charafeddine
23:43
ABAIM and MIS workshops were really monumental in shaping my understanding of AI in Healthcare.
Panida Piboolnurak
24:12
Our brains are also black boxes.
Avneesh Khare
24:22
I totally agree with you Fatme!
Piyush Mathur
24:29
Great questions Tim.I think the issue is that we are too early.Just like 20 EHRs and 100s of deployment and IT centers, this will also evolve.The cost-effective models will survive.
Arlen Meyers
24:52
https://www.fda.gov/medical-devices/digital-health-center-excellence/software-medical-device-samd
Piyush Mathur
24:57
Also,Darwin will hold true and it will be survical of the fittest
Avneesh Khare
25:02
Great insights Dr Piyush
Piyush Mathur
25:41
Thanks Avneesh!
Avneesh Khare
25:48
Even though it is full of cognitive biases, we trust it
Alfred Ma
26:06
Clinician needs to communicate better and more with data scientist.
Zaidon Al-Falahi
26:09
@Arlen So should we hold AI algorithms to higher standards, somewhere near that of devices? I personally do think so to an extent
Piyush Mathur
26:10
Aren’t we all biased!
Piyush Mathur
26:49
@Alfred - I agree
Piyush Mathur
31:23
Eric- great question.The answer lies with development of CPT codes.I can elaborate on it being a member of AMA’s CPT editorial committee
Robert Hoyt
33:04
There is now a CPT code for AI in Radiology but who will pay for it?
Piyush Mathur
35:20
Stay safe everyone.Another amazing session.Learnt a lot.
DOREEN ROSENSTRAUCH
35:25
Thank y‘all! . Stay safe!
Avneesh Khare
35:46
Thank you MIS and all the great speakers and panelists. Had a great time!
Robert Hoyt
35:56
Thanks to attendees, presenters and moderators for a great first day
Mohammed Hassan Mohammed
35:59
Thank you for great talks and discussions
Avneesh Khare
36:14
Its 2am here in UAE. Have a good nite. Stay safe!
Ernesto Rivera
36:33
Thank you all. Great discussions.
Tim McLerran
36:38
Another incredible day with the MIS crowd. Thank you all for your insights and camaraderie!
Pele Yu
36:47
Great course programming, very diverse perspectives, its very inspiring to see you all!!
Piyush Mathur
36:47
Stay neural networked everyone!
Panida Piboolnurak
36:47
Thank you!! Will see you again tomorrow.
Ben Babu
36:56
excellent session ! thank you
Avneesh Khare
37:01
Eagerly looking forward for the Day 2 tomorrow
Fatme Charafeddine
37:29
You all made my day :) Thank you so much! Looking forward for tomorrow
Debra Beauregard
37:34
Great meeting today! Thanks Julie and David for all of your work behind the scenes.
Zaidon Al-Falahi
37:37
I attest to that Anthony! Thank you for the opportunity
Alfred Ma
37:38
Thank you and looking forward tomorrow.