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i mean i i think seventy minute wins and um to remarks up phone device stared you
love that and we do this because i lost my glasses on the way here
at and the second reason of course is i'm german norse agenda so does my happy face so i have nothing against you
that's just why yeah i always like to start i understand you have a ah number
for interesting talks only behind you and i want to start a small exercise
um that helps you to me dude your brain a little bit if it's called
mind wondering it requires that you put your phone just away for a second
get up straight in your shared maybe go with the shallow that back and make eye contact with me for it
wait for translation but i can see you all please take justin seconds to make eye contact you sit up straight that's very important
make eye contact with me
and we all closer nice
and you think of the person that is most important and most other than to you in your life
great image in your head of the person
maybe you wanna smile maybe not
and you open your eyes again keep that image
if i close my nice i seem under front of um a good luck for me no
and i live very very easy simple principle my life happy wife happy life that's pretty
hard to go buy a if you are from the syphon from pain every day
because when a matter five years ago should last actually since you last fourteenth
and as a good portion that was going for the doctors and and
it took care five years twenty two visits to the doctor for
to come finally to the white your nose is in the treatment between as was done for easily was actually and the mitre wasn't
and combination dropped was intolerance so almost with and and if you would like to say so
but however people overlooked wasn't taken seriously and was not treated the white whale
and my point is if you don't know what you have a
few diagnose is not on might know treatment can start whatsoever
so we believe getting the treatment getting diagnosis right is the most important part start in the white house journey
and we believe that is a problem for number of reasons and one no one
can really hard hard to argue if it's just the sheer number of complexity
so we have tons of symptoms thousands of known disease
and just the simple fact that a normal doctor can maybe have one thousand one thousand five hundred of them in his head
and no one is white men would make the point is you can actually we oversee all kind of red it's nice
and if you consider that complexity always make an um example on one show 'cause it just a member everyone of your image your hat
you would print it out as a possible you know like this this kind of presence you get for your spouse when
you have not that idea and we all in this room which take is possible and turn it to the floor
and then ask someone to put it all together back again because just sometimes symptoms fitting to different disease but you
don't know what you're looking for up to the top of going to deposit light is actually very challenging
we believe that technology can help with that because it helps the doctor to
oversee the complexity and allows him to come to light it says
there's emission of later we believe it is a fundamental right for every person on this planet to get to my joke noses
and then just started like different and we believe we're here to support patients as well as doctors
how we view it
we do that we and application does called a got checked if it's in a i based chat part
that allows you to gather information into a series of questions lead you to differential
diagnosis that tells you what might be the best fits forces into thing
there's a second product should call a uh for doctors which allows exactly the same uh engine but with a different
approach because if you're patient they wanna take being hand by hand because it's the subject if you're not real
you don't care particularly much about disease definitions and symptoms
but if your doctor you don't need to be taken by the hand actually see patients walking to the door and have already
pretty good first imaging maybe you just the one or two flops uh to be sure to you deserve a user flow
but the interesting part is not how the product is journal part are to the people interesting parliament focus on today's how it works
because they i think they dumb machine learning all passwords nowadays that have been following
aunt conferences we started working on this actually back in two thousand eleven
we started to fifty doctors netting out every known centre
make sure that every known disease and adding probabilities to read based on the
um medical research and the shadows up there and constantly updating those
based on that we visit developed a neural network that is then put forward fifty patients input data
to it and then be very fight it still have medical experts in the in the background
so we strongly believe didn't approach entirely focusing on data
algorithms would never work and the little good results
again a simple picture to illustrate that um if you just take data and generalised experience
you might end up with some general rules but as what have we have done in the middle age you know generalising experience
we believe you need a very fine experiment object the full truth in order to
make progress and uh chief the number one level comes you want to have
so you have to strangulation of approach of the medical experts you have the data and then you combine of that but
i mean not go into the details of that but explaining a little bit where we start so
you have the possibility nader to get symptoms like direct information from the patient all the doctor
but could also start early and get on health information jean data yeah data
to be you know change the probabilities the likelihood for certain patients how certain sentinel disease
an easy example someone uses ada in africa malaria are is a much more
likely case and if you use it for the same sentence in europe
what then happens is not the pasta tendency of questions so a
that is not fixed and focus on pushes you certain direction
what we do is we asking you questions in order to minimise the possibilities
rooms for diagnosis that means of every question eliminating thousands of options
and because we do so we are able does not very important to show
you transparently in the and why we have come to certain result
because of course nobody's forever also i wasn't so i'll use needs to
be able to be transparent unexplainable to its doctors and patients
and shoulder way of reasoning to spot mistakes and also maybe um for example if the pay she you know
uses along information doctor should be able to go back and say that this information needs to be changed
what then happens is become one of the one too fancy have despotic regimes we come
up with a differential diagnosis that tells you what is the most likely fit
to your conditions and what is the most um probable
that means arises for example is not very common so it's not very likely that you have it
but very often it's the best fit to explain certain um patient um
case that's also the reason why the most often overlooked because if you have to treat hundred patients but day returning
to what what is most common and what you see normally every day and most of the cases your light
if you look real deep it is unfortunate is print is not very big
a little bit here is is in the end how information accessed
mean reprocessing thousand tolls of of data points and information and
in the end we illustrated in a very easy understand the car for the show what are the most one sentence
to which condition this speaking to and you see the figurine like like what is
like very fine a certain properties and what is falsifying sort of budgets
and if that's simple trick let's say we are able to choose huge number
of complexity and make it accessible slow for patients also just for
we didn't them off validation studies pilots and its appearance of that don't want to show you one particular one today
some of the medical university of an offer and the idea was what
would happen if we choose doctorates from the last ten years
and gives the same information the doctor has written down to a data and compare the
results to the actual outcome and of course uh you would suspect it wouldn't be
here on this conference it was not a success allies the most dramatic case we found
was mister k. is the case for symptoms first started in nineteen ninety five
starting getting treatment in two thousand two thousand one and was diagnosed in two thousand fifty
up to see very very long painful john doing discourse um he lost his job about depression
um i got divorced and had actually very visible um life and uh uh you explain
it the most middle part for him was not knowing what was going on
after being widely diagnosed however treatment started life signifying proved
i don't for this case we found that a that would be able to find the
right there course like you did before related disease already in two thousand one
i don't claim that that would necessarily automatically to the white feet in in two thousand one
but would would have been a very good friend for the treating doctors that if
the you know the first iteration doesn't work maybe to look at this direction
on average we find that around seven years of stifling on for finding
and to find a lighter those could be saved a using technology
actually i we won't doesn't out from university cleaning often over to five more years clippings
who skip that part ada has been compared to of course the competitors validation
studies will most people found over and over again is that our curse
a little much higher and the covering much much more disease than our
competitors i think the main reason here's why you is our history
course it was founded coming out of the max planck institutes and how many news foundation
so uh background is in signs not necessarily business so i was not
set up to you know make a fortune or make fast except
our phones that reason but i i do your that way of disease are
where but if you think of it is that ten percent always combined
you know make up a a tort reform two hundred million of all the dust silently suffering
among us he what's considered this is like sub saharan africa that's the minimum wage
just because you could con put them all in one place and make it visible how much is people suffering
uh not enough money is that cater to research and treatment and support for these people
but of course the technology has no use it's not used so we looked into case of energy hasn't worn out
in u. k. for example the number of clicks and show like two patients actually want to use that
i found yes even elderly people will say okay stare approach technology not different from young people are we
found that the oldest i'm actually at an shouldn't eighty eight is exactly but doctors next important question
we found it is and get 'em numbers positive feedbacks from doctors
using damn windy because all claims not that we want to
replace the doctor our claim is that we hope him very difficult
unchanged ration um to help us patient the test extent
where he was standing right now few numbers so we have around approximately so
to just thirty five thousand patients coming in every day so we have
i think i always updating dislike but never get a to this day
the scroll thing right now for five point four million assessments
and in there to see the number of instruments is lower that means we have a retention week of
around thirty percent at the moment so people actually use that i find it useful and become
we have around ninety thousand positive uh feedbacks and um relation that patient is also how we
is a very important channel loss of getting feedback people very often um tell us i went to
ada at the writer president adopt and he actually said it was exactly what data suggest that
does that just number of examples from people were getting
i'm always make this show control if you have a bad day just go to the user feedback
and we to it uh that's very motivating um but of course
it's at the moment um uh because all anecdotal evidence
so we don't have yet i'm a systematic approach of tracking patients to complete have system
we working two words that are popping up of health insurance and fifth operations
so we just signed to speak for example of the largest health insurance in germany plastic or can cause a lot of women
that would allow us channel to get the feedback automatically folder i'm
sure people back was on ten point four million people
do you ski is a very different so it could be used um to improve the quality of care
it could be a great tool of linking also solution is to improve the um cheap enough
clear the future of pull tractor or if the disease management especially for chronic disease
and could be of a great way of finding patients to do by choice at the time
we basically see it as an i'm substitute for just getting your symptoms and wanting to the
emergency uh because you think you have you know can send your time next day
for the doctors um of course the most important decision support
um but we also believe it could help to use on the
steaks and open up having of cases button colour put together
and of course data could be also very useful part from abusing other
technologies so we know jehovah's advancing very fast speed up it's
okay and um do the question was how do you have that complexity and how to you as a doctor
um we don't have time to dive into everything the solution how do you decide which to work with machine part of
we wanna number of prices i was forced to have the slide in here
i don't think it's perfectly useful um more interesting is maybe where the joining going to words to
and and just previously the hurt already of the power of including
genetic profiling um work on that as well because we think
the possibilities there the question of how we're gonna use it in every day practised and we believe it's gonna be very hard
uh for doctors to makes it even if you would be finally make
the stuff of making patient information available at all times and everywhere
how do you assess that if you have an average seven eleven minutes to do for patient if you're jennifer just
we could help with that because all probability models would allow that every single bit of information are getting so
loud change the probabilities and then you can very easily show you what to do with that information
no no we mention it will be very passionate about is um building
alliances um to how to detect and map out where disease
we all to make you believe that the trend to what's personalised medicine what actually
turn almost every disease into where disease if you like to say so
also just very nice example we all different from the outside most likely all different from the inside
and at the moment we half of course to time resource limitation we have a one size fits all approach
and we think this was can change if it's gonna change also the treatment is gonna
change and so where diseases in the moment the end of next for topic
but the thing with the things we gonna learn there again ultimately benefit of us
thank you very much for your attention
and i apologise up front icon speak french i have french different once but it may be worth
mentioning crucial problem you can ask enjoy can get there yet transit with so many question
so we would stop on the left side and then the right i thank you very much for presentation i was
just wondering what is the regular three stages of the
project of your or your medical devices diagnostic tool
oh you see by regulators basically that's um that's a good question we
certified as a medical product um be to try to um to
x. think very carefully what we do that this is not an substitute for going to the doctor speech is a suggestion
in most in most like cases take this and go to the doctor and
get proper care but engine you have a very special so every v.
we're at the moment in u. k. in germany and us and have
number projects wanting in tanzania kenya and look into our market so
i'm in germany to situation that or it was all base is quite different because
we have the whole from distant now once we chancellor you heard of that
and so we have suddenly a situation where it feels like everything goes
so to form insurances to hospitals doctors everyone feels like we have waited ten
years we've debated a long time now is the moment to move forward
where you normally would feel traditionally you will fit a lot
of resentment and be very have very for careful steps
now and you we feel that right now it seems to be the momentum everyone wants them for that
thank you lot thank you for your your talk so in terms of actual objective
performance can you share some numbers on how well you were your machine operates
um you need a a lot of accuracy light accuracy your
information or anything like that yeah um it differs differs
depending on the disease on the condition and the environment numbers and the quality of information getting
we have performed around seven validation studies and the low was strange was thing seventy six percent
and then the best cases was up two hundred percent you know depends on if you wanna detect or
fever or you want to detect uh uh caps um
i also to think it's would be um too much simplicity to say we have to soccer sort of
of ninety percent and it's just it's just not true depends on the which discipline you look at
and it depends on the quality of information we have another ten politicians something's coming up
uh to look at different fields because we think it's a very good way to learn and
if we often often get confronted what happens if you do a mistake you
know you don't have hundred percent so obviously also ah sometimes wong
and i have to openly admit where a uh house i'm still to the
works especially when they have come abilities so when you have you know
several disease interacting with the java because that's very hard to model and a certain extent
but the reality is also doctors not hundred percent and as long as we're working in partnership another displacement
we feel we adding much more well you may causing harm also we didn't have a single cases someone was
mistreated and you know something that happened he was not treated uh in a certain extent so we'll
i think hope that answers your question if anyone's interested i'm happy to send on after
it's more slides on the validation part as well okay thank good next question
used to go to a question techniques we've talked with the first one is the no if
the uh you're probably double will probably do tricks is it available for p. beatrix
um dashboard is freely available for everyone and it's used with
the doctor version it's not willing to sit and um
um i feel that i think paychecks behalf project going on in the nick at the moment
but there we are not in the rolling out face yes the the pardon face
not because the product is not ready but because the infrastructure is not ready
you know because if you put it in a in a in in day practised and you just know where to
put in the data and you know do something with little reported back um that's gonna be difficult um yeah
so yes but in that it okay the next question who who who profess stuff e. n. c. i.
we're still working on so we know that challenges that you have a new one be probably be
the beat and a lot of hype but because we lack date now where we
can make sure yeah q. i. e. like rachel and you get ready
so we have an x. that upbeat unfortunately i review of their biggie like we could name
oh the second show the like poor performance for now
probably that we may come when i but i see now i made sure why
let me think about now in full of not
i thought we should have yeah you put o. e. cool
there's no question i'm most afraid of because i know we have a pretty good answer for that
but i'm just not the right person and you see a a eight iverson very interesting
antidepressant gee i have people coming from the data field machine learning but also medicine
and for example this particular problem or head of research would be perfect johns it um but i would have to say
please send an email and i will fall off of that on this in that i would try a simple and
this is the answer is um if we put in objectively data like lab tests as well and so we not
we line alternately only on experts and we half by by
now five point four million cases to verify against
thing we have stocking with most just that the madison treatment
and also um possible turkeys is also culturally present so
if you look at fox on the tropical disease which we do now enough uh current and then yeah especially
um you can't have the same probabilities and the same suggestions like you have in your
so for example this a star of working refill for positions and yeah
to prove that the situation and also the corporation the flat just provide us
thinking and i wrote me and also tanzania this will take time we're way of the challenges and if you wanna
go deeper i invite you to write an email then happy to link you had of research thank you okay
you should really try to have both the big videos you put the which shows report we the with the
tomato collected goodwill much the both of those limits you know thank you were which will be the fish

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Conference program

Mots de bienvenue
Sébastien Mabillard, CEO | Swiss Digital Health
15 June 2018 · 9:07 a.m.
Mots de bienvenue
Victor Fournier, Chef de Service de la santé publique | Canton du Valais
15 June 2018 · 9:11 a.m.
Mots de bienvenue
Jean-Albert Ferrez, Président | Fondation The Ark
15 June 2018 · 9:19 a.m.
Mots de bienvenue
Laurent Sciboz, directeur Institut Informatique de Gestion | HES-SO Valais/Wallis
15 June 2018 · 9:24 a.m.
L'écosystème d'innovation ouverte du CHU Sainte-Justine: une grande communauté gagnante!
Kathy Malas, resp. de la Plateforme de l’innovation et des Fonctions des maladies chroniques et aiguës | CHU SAINTE-JUSTINE (Canada)
15 June 2018 · 9:33 a.m.
Les livraisons par drones : vers une amélioration de la logistique dans le domaine médical
Janick Mischler, Program Manager | LA POSTE SUISSE
15 June 2018 · 10:07 a.m.
E-health et intégration des soins
Marc Cikes, CEO | MEDBASE ROMANDIE (Suisse)
15 June 2018 · 10:32 a.m.
Questions réponses
Remi Gauchoux, Business Development Director - Carenity
15 June 2018 · 11:46 a.m.
Futur de la santé mobile
Dr. med. Patricia Sigam, CEO & Co-founder, digital Med-Lab
15 June 2018 · 11:54 a.m.
Democratizing Data-Driven Medicine
Tarik Dlala, VP Marketing, Sophia Genetics
15 June 2018 · 12:14 p.m.
Ada inside
Vincent Zimmer, Ada Health, Berlin
15 June 2018 · 12:39 p.m.
biospectal, the optical revolution in hypertension monitoring
Prof. Patrick Schoettker, CMO. Biospectal
15 June 2018 · 2:06 p.m.
3D Printed Medicines: A Digital Pharmacy Era
Sarah Trenfield, MPharm, Senior Formulation Scientist, FabRx Ltd.
15 June 2018 · 2:23 p.m.
The Digipharm experience
Ahmed Abdullah, CEO & co-founder, Digipharm, Basel
15 June 2018 · 2:45 p.m.
Enabling the rehabilitative revolution
Dr. Manfredo Atzori, HES-SO Valais Wallis
15 June 2018 · 3 p.m.
Team Gamified Multi-sensory Stroke Rehab
Jean-Luc Turlan et J-P. Ghobril, Lauréats Arkathon 2018
15 June 2018 · 3:22 p.m.
Secure and Trustable EMR Sharing using Blockchain: Open Challenges and Lessons Learned
Alevtina Dubovitskaya, HES-SO Valais-Wallis
15 June 2018 · 3:38 p.m.
Conclusions
Sébastien Mabillard, CEO | Swiss Digital Health
15 June 2018 · 3:59 p.m.

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