Welcome to AI and I tier the video podcast series. My name is Dr. Ray Han Ahmed. I am so excited today to bring you a good friend, a colleague and really a mentor of mine, Dr.
Hunter Sherwood, who serves as vice president of political services and technology and a well and much admired organization called Orbus. If you haven't heard of it, please check out Orbus.org online. It's a wonderful humanitarian I tier organization. Dr.
Truer did his undergrad at Duke, he's an optimology resident at Emory and he will tell you a story about how he got into Orbus and global optimology. Dr. Truer, thank you so much for being on the podcast today. I really appreciate your time.
For our listeners and our viewers, I'd love to hear a little bit of background about you and how you got to where you are today. Yeah, so first of all a huge thank you for that introduction and giving us an opportunity to talk about Orbus and the work we're doing in the AI space and how we're trying to democratize both distance learning, telemedicine and AI. So I started getting involved in global health as an undergrad. I had an opportunity to live in Kenya and I knew that I wanted to do global work.
At first I thought I was gonna do infectious disease. Then I thought I was gonna do orthopedics and specifically hand surgery and then I saw cataract surgery and I'm like, this is it. And I saw that literally you could transform a life in a family within about 10 minutes. You didn't need an ICU, you didn't need blood transfusions.
And I was watching incredible microsurgery which I love from hand surgery applied to the eye. So I was very lucky I got into Emory and while working with a great class, always was focused on global work. I actually got to go to Ethiopia as a final year resident. And then my last day of Emory, I turned in my pager at 5 p.m.
And I flew that night to join the Orbus plane which was in Western China at the time. So for me, I've had probably the luckiest person I know and I'm living the dream I never dreamed of. I never thought when I went off for college that I'd be doing this work, certainly not running clinical trials in AI or working with some of the best professors from around the world. So Dr.
Jorbi also probably one of the most modest people I know, you know, you don't have a few social media presence, but if you did, I think with the literally all your accomplishments, he is also the American Academy of Optiology, humanitarian designation for 2021. So congratulations on that. And you're silent and multiple articles and newspapers, most recently New York Times with the passing of Dr. Payton, starring at Orbus.
So give me a little bit more of Orbus, Dr. Patton and the famous sort of airline that I spoke for. Yeah, so David Payton, I was very lucky. I got to work with him and I probably learn more from him in one hour than almost any other person.
This guy was a million ideas a minute and he came up with the concept of Orbus in the 70s and at that time we didn't have the internet. There wasn't a lot of global participation in conferences and he wanted to create a flying classroom. And this is just when Intracular lenses were taking off, excuse the pun. And what he wanted to do was get people to move to Faco, to he really wanted to stamp out a fakia, surgical a fakia.
And so, he was with friends in aviation and said, wait a second, I could just put a classroom in a plane and go around the world and demonstrate and work shoulder to shoulder with the professors and expose them to the latest techniques and the latest technologies. I can tell you his passing, we lost a giant in global ophthalmology. And as I said, I still go back and look at my notebooks when I would sit with him and I would feel literally four or five pages in a lunch or an hour and a half coffee. You run across people like that very rarely in life and I can tell you I miss him already.
So tell me a little bit about how Orbus is different from, there are a number of other really wonderful iCare organizations around the world. Orbus has a maybe a different approach in terms of thinking about skills transfer and how to create sustainable changes in society. Tell me a little bit about Orbus's philosophy and the approach. Yeah, and I love the field of global ophthalmology.
There's so many great people and organizations out there. I think what differentiates Orbus, other than just the flying eye hospital, we're focused on technology, whether it's simulation, artificial intelligence, telemedicine, certainly training, that's kind of our core focus, especially subspecialty training. I think a lot of organizations and rightfully so are focused on cataract. We're focused on biomedical engineering, anesthesia, pediatrics.
So for me, it's a very subspecialized training group and then treatment. One of the things I'm always fired up about and I always talk about is Orbus distributes over $200 million with the Zithermex a year from donated, from Pfizer, from the donated an antibiotic to get rid of Turcoma. It's really exciting that we as ophthalmologists likely will see the last Turcoma case of active Turcoma in our lifetimes. So, you know, I always tell residents, you're so lucky you're in ophthalmology.
We're the most innovative field bar none. First field to have FDA approval for autonomous AI, first field in all of medicine to have gene therapy and in our careers, we will see diseases like Turcoma be something of the past. So for me, there's never been a better time to be in ophthalmology. There's never been a better time to be an ophthalmologist.
Orbus was a great fit for me. I loved learning and I loved teaching and every single one of our programs is a skills exchange program. I didn't see Turcoma as a resident. I didn't see rubella cataracts.
When I went to Ethiopia for the first time, I literally saw dozens of cases of Turcoma and my first cases rubella cataract. For me, I've been now with Orbus about 20 years, roughing on and I can tell you, this is a constant classroom, a constant learning experience. And I get to work with amazing volunteers. We have over 400 volunteers from over 32 countries.
Some of them are nurses, doctors, anesthesiologists, biomedical engineers, eye banking, ethicists, artificial intelligence. To me, that's what I love is that Orbus provides so many platforms for so many talented people around the world and using the concept of connectivity. It used to be the plane to connect people. Now it's the internet and AI.
For me, it's really harvesting the best talent and globalizing that and distributing it around the world. Yeah, I love the concept of connectivity because that fits really well with how I think Orbus thinks about data and also publishing data and classroom instruction. So tell us a little bit about CyberSight, CyberSight AI and maybe just broadly on how you feel. We'll get into this but AI can really help particularly resource constrained areas where the potential and possibility for AI and ideas.
Just trust. Yeah. I love that question. I think at Orbus under the technology piece.
So there's three teas to Orbus, training, technology and treatment. So with the technology piece, we're always looking for novel technologies that can reach the bottom billion and empower those healthcare professionals and give them force multipliers. We see artificial intelligence as that opportunity. Over 20 years ago, a very talented pediatric ophthalmologist, Gene Hevelstin started working with Orbus and Cuba.
And when he got back, he wanted to continue mentoring those doctors he had taught on the plane through the internet. And that was just when the digital cameras were coming out, very pixelated, not high resolution, but they were perfect for strabismus. He could see whether or not there was a vertical or a horizontal strabismus case. And so he started the whole field of telemedicine with strabismus.
He called it cybersight and started that team at Orbus. We now have grown where we have distance learning. We have our own in-house AI team. And one of the things I love is how we've taken Gene's telemedicine and now it's gone over 40,000 cases.
We have over 900 cases of retinoblastoma. This is peer to peer telemedicine, not a grandmother asking about their grandchild's glasses. So for me, both the plane and cybersight started with one incredible ophthalmologist. And both of them wanted to connect the world and find ways to mentor people from around the world and also give patients access to the best possible technology and care.
Tell me a little bit about cybersight AI in particular. So right now at this period, I know you've published a ton on this subject most recently. I think in British Journal of Automology. And you guys have a really credit to the organization, you and all the, I know you were surrounded by a bunch of very, very talented people.
So walk us through sort of key sort of lessons that you guys have learned sort of over the past, I don't know, five or 10 years. I love cybersight AI in particular. So I love every day I can get on the dashboard and see how cybersight has grown overnight. We have over 110,000 registered users.
Some of them are ophthalmologists, optometrists, nurses, biomedical engineers, residents and students. We're in every country in the world except for two. And one of the things I love is 24 hours a day, seven days a week, we offer a telemedicine consult service. In the last few years, we have developed an in-house AI that can do adult diabetic retinopathy, glaucoma and macular disease.
Now you will see one of our papers, it was done with a trial called ChildStar from Bangladesh where our algorithm was actually also shown to be very effective in children. So we, that was retrospective, it was not actively involved in direct pediatric care, but was reviewing retroactively cases. We've seen AI as a wonderful tool for global ophthalmology. Like any technology that needs to be studied and that's why we always do it in research, our head of research is Dr.
Nathan Congdon, he's based in Belfast. And the head of cybersight is Jonathan Stollard and the AI architect, his name is Nicholas Jacard. I think you can tell by the way I talk, I'm not God's gift to research and I'm certainly not God's gift to tech. What I'm very good at is connecting those talented people and those technologies to the partners and the patients who need it most.
We have launched, and for example in Rwanda, during the height of COVID, we launched AI in a clinical trial, it's called Raiders. You can look at, we have a few papers published on this in a few presentations. And certainly we're looking at the accuracy, the sensitivity and specificity of the actual diagnostics. But we actually looked at two other things.
How did AI diagnosis improve compliance for referral? So that if someone was the found to have severe diabetic retinopathy, they would actually show up to get treatment. And we actually showed that AI improved that process. We also looked at both sides of the healthcare equation, the patient and their family and the provider and both sides of the equation loved it.
So we have found that AI is very welcomed by both the providers and the patients and their family. We have trademarked the term of machine mentoring, not machine learning. I think you'll see a lot of organizations are going to low to middle income countries, harvesting a lot of data and not always leaving behind cameras and programs and partners to continue on that care. Ours is just the opposite.
We're now using AI to mentor the technician so that after they take the fundest photo, they can see the glaucoma, the diabetic retinopathy, the macular disease, it highlights so that it's not diagnosed synodios, it's actually showing them on the screen, where is there the vertical cup to disc ratio, where is their macular edema. So we actually use AI for teaching, not just as a force multiplier for patient care, but also for technician and nurse training. I love that term, machine mentoring. Because it really highlights, especially, you could be done here too, in terms of for resource rich areas as well.
The idea of doing this in a resourceful strain area, maybe it's not even an eye care provider, I can imagine. And I wanna highlight the other point you mentioned, which made some, we may have missed that, and here it's right, so if they're told, in a sense that they have diabetic retinopathy, they're told at that same visit, is that correct? And then are more likely to then go seed specialist. And it's also explained to them.
So I think that there's two reasons why we think the compliance for referral is better. One is the immediacy, they don't have to wait for a human to over read. And then five days later, try to find this person who's gone back to their village, things like that. The other is that the technician can now explain things to them as well.
So for us, we see AI as a wonderful screening tool. We see it as a wonderful teaching tool. We've also looked at how AI can improve physician productivity. You're a doctor.
You know, especially in a very busy retina practice, you only want to see patients who need procedures. A patient who has no background disease, doesn't want to wait three hours, be dilated and all that. They want to come in a non-dilated picture, and 10 seconds later, they're out the door. So we found that AI also improves retina productivity, where the doctor's chair time is better spent with patients who actually need their procedures, injections, lasers, and surgery.
So that's only on the hypothesis for patients. Exactly, maybe in the country, yeah. Exactly, you're exactly right. I mean, we work in countries where there's one surgical retina doctor for the entire country.
So we better get that chair enriched with those patients who really need to see that one doctor. So yes, we at Orbus, and again, this was led by Nathan and another team member named Noel Whitestone, we looked at how AI improves patient satisfaction, patient understanding and referral, as well as physician productivity. So certainly, I'm very proud of the team, because I think when you launch a new technology in a clinical trial, it's taken very seriously. It's not a toy, it's not a gimmick, it's not a shiny Christmas or birthday gift that they open, and then forget about a week later.
So we've studied almost all of our AI programs in research trials or research programs. And just to reiterate for the audience, a doctor say in India or Pakistan, which is in those two examples, not ours, can go on an upload, is this right, can upload a picture and CyberSight AI to help with the diagnosis, is this rare? Yes, so for the ophthalmologists in the group, if you go to CyberSight, C-Y-B-E-R-S-I-G-H-T.org, CyberSight.org, you'll see that it's CCC, not the continuous curvy linear or capsule of Rexis. It is content, we have live webinars, where sometimes we have over 100 countries watching live, as well as archive content in the eLibrary, which is the world's largest freely available library for ophthalmic learning.
We have courses, these are structured courses in everything from retinoblastoma to genetics, to very basic small incision cataract surgery, and then we have consoles. So if you register for CyberSight for the consult service, you can register and get consults that are AI enabled, or direct human to human cases. So for example, if you're a medical retina doctor and you wanted to see whether or not this patient needs a PRP or laser treatment for diabetes, you can enable the AI and get an answer within 30 seconds, and then a human will also come to provide human mentorship to talk through things, because the whole purpose of Orbis and CyberSight is human resource development. We are not trying to use AI to replace doctors, we're trying to actually maximize their impact, their teaching, their training, and ultimately their treatment.
You're hearing a term in some bandy groundhog, that AI is really not artificial, but more augmenting intelligence when it comes to healthcare. Exactly, we see that as a force multiplier, so that the patients, the providers, but also the rural community health workers all benefit, that this is going to impact what we're all trying to achieve, better outcomes, better care, better access. I do think, and we've talked about this before the podcast, I see a very bright future. I'm not naive, I realize every day, there's bad things on the news, but as I said, every day, I'm seeing what AI is doing for good, and how, you know, when I first went to Kenya, I never thought I'd see my host family again.
Now, over 95% of Kenya has access to a phone, there's more people having access to the internet than clean water. I think very soon we will have low cost, high fidelity cameras, that you're going to be able to do field screening and be able to do things I can't even imagine right now. So yes, I'm not naive, the world has a lot of problems, but I would also say we are realizing technologies that I would have never guessed what have happened in my career, gene therapy, autonomous AI. I mean, we're now talking about robotic cataract surgery.
Yeah. I never would, I mean, I would have told you that was so much more fiction than science, now it's not sci-fi, it's just science. So I'm a data-driven optimist, and I love the fact that our research team or cyber site team, our country programs, every day, something in my inbox inspires me to say, wow, I never imagined X. And that's why I think in the next five years, the next 10 years, by the time I retire, the entire field of global ophthalmology is going to be revolutionized.
You mentioned data in a digital technology. I love that phrase. It's the always phrase. By the way, they're all trademarked and copyrighted.
So yes. But, or how do you guys think about data? Because we talk about data being the new oil and a lot of these models are sort of converging. We see that from the large language models a little bit.
Maybe there's sort of marginal differentiation, but with Orvis, with the boots on the ground approach, you all have access to data that others probably don't have access to in terms of the data sets that you have, a very different form of sort of messadore online. Think about data that are not particularly particular in other things. So what's your thoughts on that? And the data?
Yeah. I think there's two divides I worry about. The digital divide between the haves and the have-nots and the data divide. Are we being globally represented and having inclusive data sets as we train algorithms?
So that if you have a cup to disc ratio of .65 or seven from Ghana or West Africa, the data set and the algorithms will recognize that and not tell you you have glaucoma. I do not want data poverty. I want the bottom billion to be represented in algorithms. And I think that's one of our core missions at CyberSight and with our AI platform.
So absolutely I want to close the digital divide and the data divide. So there's equity and representation in algorithms. So they're not just trained with one cohort, one country. And you're right.
We're doing AI and reaching communities and villages that I never thought would be possible and making sure that data is included. And those patients do have access. One of the things that drives me crazy is when I hear that, oh, ex-company did such and such in country Y, but then they never left anything behind and they did not leave something for the community that helped build that product. At Orbis and at CyberSight, it's just the opposite.
Our whole focus is low to middle income countries. Our whole focus is empowering those communities and the local health, iHealth providers. So for us, we absolutely want our algorithms to be globally educated, globally represented, but ultimately globally distributed. To me, making a product that helps the top 1% doesn't really interest me.
And it's not that challenging a problem. I'm much more interested in how do I get this to the most rural part of Ethiopia or Rwanda or Vietnam or South Africa. And we all know, and you see this, I'm sure, in your hometown with so many displaced persons, there are now people in New York City who have blinding eye diseases and have no access to diagnosis or treatment or referrals. I want to solve that as well.
Yeah. And the more generalizable the data set is, it's better for these private companies as well. If they're able to access that data, what can I mention? They're gonna be seeing patients who hail from these regions, if not in that particular country of course.
Absolutely. I don't know of a successful company today that doesn't think globally, that wants to access every market, access every patient. To me, that's what I'm most excited about with AI. I know that there's certain eye centers where the chairman sees the donors and only the donors and how much time they spend with them is based on what percentage of giving they give.
What I love about AI is you get the exact same accuracy and the exact same read, whether or not you're the wealthiest person in the world or someone who doesn't have two pennies to rub together. To me, that's what equity, where you're representing people, providing access and providing the same level of diagnosis, whether they're the richest person or someone who has no means whatsoever. And I do think we're achieving that with CyberSight AI. Now let me be clear, are we perfect?
No, that's why we're studying in research. We're always trying to make a better product, a better program, helping our partners more. I think one of the things that I love about CyberSight is we're constantly asking for candid feedback from our partners to make our products or our programs better. I always tell people compliments are nice, they actually don't make you better.
If you wanna know the best compliment is giving someone candid feedback that is constructive and makes a better algorithm, a better camera, a better program, a better clinic. So we do a lot of reverse innovation where we're taking the feedback of these incredible things that our local partners are doing and educating our programs, our technologies, and ultimately what we do at Workis. You know, as part of AI and AI care, we try to connect with three owners of AI care, our primary optimization. So for our listeners, they wanna get involved and think about from those with different fields, how can they get involved with Workis?
Where would you suggest they study? Yeah, I think it's always first, you know, thinking about what are your gifts. So I work with a lawyer who doesn't know the first thing about ophthalmology. Their gifts are ethics, informed consent, patient bill of rights, and we've distributed and left those templates around the world, and guess what?
That sometimes has bigger impact on patient care and what the patient experience was like than any little technology or technique I can teach with my hands. So I first always ask people, what are your gifts? What interests you? Do you like teaching?
Do you like skill transfer? Do you like service delivery? What is it that you're gift? So one of our volunteers, she's an incredible professor at the University of Colorado, Colorado, her name is Jennifer Patnick, her gift, she is a data ninja and she has gone on many, many papers where she has provided help to Orbis by being that research expert.
So the first thing I always ask people who are interested in helping our mission is what are your gifts? Then when and how do you wanna apply those? Do you wanna do that in person virtually? When is the best time for your career, your family, your personal health, things like that?
I like Orbis because we try to then distribute those gifts and meet the expectations of the volunteer. If you go to Orbis.org, O-R-B-I-S.org, you can see how to get involved. It's right in the upper right hand corner. How to be involved as a pilot or a volunteer or as a doctor, as a teacher.
You know, for me, some of the greatest impacts you've had at Orbis are from the most unexpected, non-epthalmic sources. A school teacher who taught us how to do a school streaming program. We had a 16 year old, he's now at Stanford, he's a genius who when he was 16, developed an app to turn an iPhone into a mobile phone into a vision chart. That's now being used throughout India as part of our program called REACH, Refractive Era Amongst Children, that now is one of the largest data sets in the world for pediatric myopia.
I love when someone who is totally different from me, a different skill set, a different country, a different way of thinking comes to me and says, I have idea, I want to help Orbis. Those are the conversations that really turn out to be game changers. So Dr. thank you so much for joining us again.
That's Orbis, O-R-B-I-S.org. Please visit their website and contact the organization. Dr. Orkhan, thank you so much for coming on the video podcast.
This is always, a lot of fun talking to you. Just as a friend and also just to learn from, I learned so much in the short time we had to thank you. Cool, thank you guys.