 All righty well good morning everyone thanks for joining us as always this is the hyperledger healthcare special engines group thanks for joining us I suspect we'll get people joining the call as we move forward this is our sixth special topic meeting as it relates to the COVID-19 virus pandemic I we're kind of hoping this may be the last of the special topic cycle and what we're trying to get ourselves back into more general meetings and part of that really has a lot to do with the fact that the the HCCIG the hyperledger special special engines group has has quite a number of other offerings and and obviously specifically we have three subgroups and those are really taking a bit of a backseat and so we're trying to trying to find a way to balance some of the work that's ongoing some of that is is COVID related but we're trying to find a way to balance that with with obviously the sort of topic the big headline that we've been dealing with for the past several months so as always this is a recorded presentation and also by virtue of hyperledger main Paralympics Foundation I wanted to pass along to you the antitrust slide you should be seeing it here please read through it in short just be aware of anything that you share here is this is open community open source and so please don't share in the IP and in short be a good person for details feel free to read through the URL that's presented here for any details as it relates to the antitrust policy already so we'll do a round of introductions as we normally do if you're new to the organization or you're just visiting it'd be great to hear a little bit more about who you are where you're from and your interest in blockchain technologies as they apply it to the healthcare industry anyone like to introduce themselves all right rich shall I start in a region sure go ahead introduce yourself yeah you'll be our speaker but yeah go ahead yeah okay so I'm the race chain co-founder snapper future tech so I'm the presenter here along with my colleague atul so we have been into we are working into boxing space for last four years now and work in various solutions for different industry and recently we have started working on a project in healthcare which I'll be talking about in more detail so it's really well focused million blockchain and that cool hyperlegion fabric excellent excellent well great to have you in ash and I believe I believe you were introduced to us by camalish and of course camalish has been part of the the the hyperlegion health care special industry special interest group community for quite some time so thank you camalish for that yeah already anyone else on the call like to introduce themselves hi so this is atul do you hear me yeah good morning atul how are you good morning just good this is good evening for us yes indeed yeah so the world is together on the zoom yeah so as a nourish pointed out I'm I'm representing the IIT council IIT being the actually coglomerate of premier institutes all across India Indian Institute of Technologies has the short form IIT and so we are doing a lot of things for the nation for covid specifically these are ongoing efforts this is not very specific to code but we keep doing a lot of other events and activities related to technology specifically and in this case we are trying to bring AI and blockchain probably together to solve some of the health care related challenging issues and the starting point for this is the hackathon which we are conducting in six different areas x-ray images being one of them there may be another fire four other different categories so this presentation is related to that activity and as we go ahead we'll explain the details excellent yeah excellent well thank you atul already anyone else want to introduce themselves tell them a little bit about what they're doing and where they're from already I do see some some regulars so good good morning to those good afternoon to those who are regulars to this and thanks for joining us as well and for those of you that are fairly new to the organization and specifically to the SIG we do keep a membership directory and I'll direct your attention to that now this is a great opportunity to just basically drop a virtual business card and and feel free to do so what you want to do is get yourself set up with a Linux foundation ID LF ID and there are details sort of on every page that talks a little bit about how to do that and once you get that you can log in and edit the wiki page directly and again it'd be great opportunity to do so great great great time to sort of share and connect with others with within the community here already so again as I mentioned this is a special topic meeting and we are focused on the COVID-19 virus pen pandemic this is our sixth in a series and and today we're really gonna have a great opportunity to speak to to rent to rent to Resh oh boy I'm tongue-tied today today they're gonna talk a little bit about their work through snap or future tech and again what you heard or just a little while ago the Pan IIT Alumni Association as it relates to the COVID-19 x-ray analysis they're using they're using AI and of course hyper ledger blockchain I believe it's fabric that they're using so so Nuresh are you ready to go I'll stop yeah go ahead and you'll share your screen and we'll go from there all right thank you rich perfect morning everyone all right are you able to see my machine I we see you all right okay you're able to see my machine right so I'm presenting so so just to be clear we can see your face but we cannot see your machine oh is it let me see what happens okay there we go perfect all right all right so let me quickly talk about the project quickly I'll just give us a quick snapshot about the project and then we'll talk about and more detail about the project then after that I will go in more technical it's not actually technical but what we are doing in blockchain size so this project is about we started this project for x-ray image analysis using AI and blockchain but the way we started working on this we realized that this project cannot be we we can use this project not only for x-ray analysis we can also do it for any kind of medical image and also the same time it could be any kind of healthcare records which could be even your vaccinations your prescriptions your lab and all of that so right now in the first phase our focus is more on x-ray image analysis and then after that it will be covered all different areas so quickly about snapper snapper is a blockchain technology innovation company we have been in this space the last four years now and worked on now various products and solutions across different industries in supply chain healthcare e-governance and our main focus is on hyperlegislative fabric and we have done a lot of work on ethereum side in the past and we have started working in CODA too but majority of work what you have done is on hyperlegislative fabric and the plot platform the product what we are going to talk about today it's on hyperlegislative fabric so what we did before we started developing a platform called a SNAP surf it's a trust protocol for certificate that's a tagline for this product so it's it was designed mainly for academic certificates in the beginning so here as part of this platform what we do is we cover digitization generation authentication sharing and verification of all kind of academic certificates but later on we realize that the same solution applies for any kind of certificates so the way we designed this so here we can use the same platform for even for healthcare and when this project came from IIT alumni association so we thought that let's try this out and we started working on this so by simply making small changes we were able to use this platform for healthcare records so the beauty of this platform is that we generate certificates or we create records we generate records through this which are efficient and automated nature and whatever certificates or records which are created through this they are permanent nature permanently secured and verification of the records can be done online and real time at the same time we are also recording all the verification which can be used for audit purpose so it basically the way we have covered everything it covers the various regulations which I talk about in later slides so the same platform we are using for healthcare and I would ask my colleague atul to talk about first IIT alumni council and what are the different initiatives related to COVID-19 what they are working on and then then I'll come back and I will talk about the solutions on blockchain and this particular platform. Atul would like to take it over? Atul? Yeah thank you Nuresh am I audible now? Yes you're audible. Okay so thanks for the quick introduction so I'll talk briefly about what IIT alumni council is so as I explained IITs are basically there multiple Indian Institute of Technologies across India and this is a collection of them they have formed basically alumni association of some sort and as I explained they they take up a lot of other initiatives so this is not the only one so they even manage some of the government initiatives like prime minister's visits outside of India their management event management etc so the last example was Modi's prime minister Modi's visit to Houston that was completely managed by this council so I don't want to read these statements but this pretty much summarizes our focus is always on technology we being the primary technology institutes and IITs are generally well known all across the globe they host various key positions like today Microsoft's CEO is IIT and Google's CEO is also IIT and so they are they are pretty prominent in US scenario Europe I don't know not much probably but they're there somewhere definitely so so this is one of the databases Narish you want to take this or I can just continue so I'll probably continue because in one of these initiatives we started setting up a very promising lab set up in the city of Bombay which is high density high population and the highest incidence of COVID positive so we were taking up a challenge to set up a lab as quickly as possible and we started even creating a bus which goes to the patients instead of patients coming to the hospital and all this lab set up so even couple of public grounds are now dedicated for the quarantine situations etc so a lot of x-ray images we understood are going to flow in our expectation was about 3 lakh which is how do you say it in 300,000 x-ray images per day all across the India we're going to come to probably one central space or one secured cloud and then practically it was impossible for radiologists to see each and every image although the clouding of images was possible even earlier the AI angle was not there and then the idea of can AI do COVID detection also came across because there were already some teams and companies doing tuberculosis analysis pretty successfully and globally we saw there was this attempt going on so we said we'll just host and hackathon collect all these themes and it is pretty much based on the Kaggle model with some variations here and there so with the scale of the images and the scale volume of the data etc plus additional security concerns because this is medical images data all this combined the AI and the blockchain and initially as Naresh probably pointed out we started with the hackathon and quickly realized that the images is a very sensitive data there were already some leakages observed knowingly or unknowingly so we are now this week itself we are beginning to control the image data as well but today the biggest plus that blockchain from snapper brings to our table is anything can be converted to a certificate can be shared can be protected for access provenance and lineage all these we can achieve with snappers product and that product was the beauty of that product was we could initiate quickly morph it into what we wanted once I understood their core architecture it was very easy to change it to our needs so we practically did that change within two weeks right Naresh so the other prominent goal mentioned below is basically related to AI so the criteria we defined for selecting the team there are definitely some statistical criteria defined by statistical experts but our primary goal was to have zero false negatives so basically no covid positive patient should go out without detection maybe some false can be taken in but that's okay and the other goal was of course to reduce the load and only or prioritize who we should take up for further test the genetic test and other tests so all this kind of came together very nicely so this shows some of the factors like four to six days to show visible x-ray effect we knew this limitation that x-ray shows something regarding covid positiveness only after four or six days of infection and we actually very very much brainstormed that how can we hundred percent really really take care of each and every case and practically that is not possible so we finally settled with practical limitations so whatever best we can do we will do but x-ray was advantageous in the sense that x-ray can travel to the patient instead of patient traveling to the machine like RT-PCR which is the gene-based test it shows probably on the first or second day the covid positivity but even there in practical scenarios there are issues sometimes it shows it doesn't plus RT-PCR tests are charged heavily because all the equipment is imported even there what they call as the cassette or something each cassette costs heavily and they have definitely increased the charges seeing the market so we are even in the process of manufacturing something indigenously that effort is also going on so a tool just to interrupt real quickly i think we have a question jonathan yeah sure yes so just to address the the challenge as far as the false positives so i think you know the the ground glass capacities are not specific to and with the ARDS to COVID-19 so there are other diseases that could present with the same findings so i think so and i think you know some of physician and so i think you know ARDS is something you actually can spot in a chest x-ray across the room so you know it may be this is a an association that you're going to find because people have ARDS when they have COVID-19 not that it's specific to COVID-19 and did you have in a way of approaching it yeah so actually we had a couple of meetings on this as i explained the statistical criteria and what classes we want to label really so so initially we started with pneumonia with subclasses as bacterial pneumonia and viral pneumonia and within viral we said it can be COVID positive or COVID negative so and then there is TB and looking at the x-ray the AI can actually classify it as both pneumonia as well as TB so that's fine we said so as long as any anybody having pneumonia COVID pneumonia and still not being identified as a risk that is what we wanted to not to have so if you do a multi-labeling or cover sometimes somebody who is not even pneumonia but he's kind of identified as do the test for pneumonia sorry for COVID that is fine some extra work is fine but anybody going scott free is a risk because he's going to spread it out in the society so i don't know does that answer your question yeah i mean sort of and i think it's just the the classic instead of a t-squared solution to this which is that you know the x-ray showing negative at the person is COVID positive so that so that maybe they just don't have ARDS so there's a viral infection they just don't have the sequela in the lungs of COVID positivity so yeah that that is absolutely possible and i mean honestly i don't have the answer to that maybe the medical experts will have some but we'll see what what is the chance is there any some indication then we'll not reject the case saying that he can go out scott free we'll probably prioritize him low but do the further gene testing and all that the RTPCR because RTPCR equipments are less there are different time delays for tests to be done but we will probably lowly prioritize that even though he's not shown any signs in x-ray but since we we combine multiple symptoms it's not just the x-ray definitely should should i move on hello yeah i think that will i should go ahead yeah so some of these these these are some of the visible effects of the initiatives taken so there is a test bus which i told about which goes to the patient then there is a lab set up at one of the hospitals specially for COVID testing then there is a lot of infrastructure donated by various IITs for HPC and various private companies also have volunteered and donated some cloud infrastructure like amazon and aws so people have come for come forward and companies have come forward in this effort so these these are the various categories we may be looking at it's not just the x-ray CT scan ultrasound RTPCR and then there are some other initiatives as well yeah we can go next so this is the bus I talked about so this has the x-rays mostly and then they are transmitted immediately and then diagnosed within maybe next two to five minutes today a lot of radiologists are doing this work eventually we'll be migrating migrating this to AI plus radiologists yeah next please uh so am i talking about this or narration yeah i'll take over yeah thank you yeah all right so so we talked about that we started with the x-ray x-ray with analysis using the AI and the main goal was not only doing the analysis we're also supposed to protect the data not only data protection from security point of view privacy also needs to be maintained and the authentication the verification of data is very very important so here uh so what we did now we are working on this project so we are creating an integrated healthcare network which will be used for efficient and secure data management and apart from artificial intelligence and blockchain technology HPC and cloud server high computing the high processing computing the servers are being used to handle large volume of data for faster processing of the records or the verification so this is a integrated healthcare network using the various technologies and the objective of this network is first of all because mainly we're talking about the testing for COVID-19 the currently the methods which are being used they're quite expensive so we want to reduce the cost the test results should be quickly turned around with the faster better accuracy and one of the major challenge when we talk about the images mainly x-ray image or we talk about CT scan or different kind of images securely they should be transported securely to different uh radiologists so data protection privacy and efficiency in the system and having the regulatory compliance is all of these are the objective for when we started working on this project so this is the architecture so in this here uh the top you see hospitals, doctors along with the labs radiologists so uh hospitals are the one who are generating data the patient goes to the hospital and they do the check up do the prescribe the medicines or to go for different kind of lab tests or x-ray the CT scan so they are the one who are generating the records the data so all of that data goes goes to the platform and we are recording that data in the blockchain network and then after that the patient is the one who's able to view those records it's the patient's data and the patient is supposed to share those records whenever those records are to be used by any doctor from different hospitals right even it could be insurance company who needs to access the data so the data is being shared by the patient so patient whenever he goes to the hospital his personal information personal data he needs to protect it uh and that is where we are using blockchain technology for that purpose that the patients are given a decentralized identifier and that is what he uses to share his information with the hospital of the doctor and based on the request from the doctor patient shares his health records and those health records can be viewed and analyzed by the doctor and then they prescribe further actions on that on the right side you see artificial intelligence radiologist basically these are the service provider who are using their AI algorithm for analysis of the images so images are transported to AI radiologist through this platform so hospitals are generating the images and they uh they go AI radiologist access those images through this platform so this is one of the diagram in the next slide which I'll talk about uh so uh here all the doctors all the users from the hospital from the radiologist or the patient to the labs or uh even it could be insurer or regulator so they have to be registered on the network and each one of them is assigned uh with the ID which is a decentralized identification number and that is what they will have to use every time whether creating a health record or accessing the health record and we are also recording whoever is accessing the record so that we can use that for auditing purpose whenever any regulator would like to understand who who are using the data so this is a yeah can I add yeah please please yeah so when we say the data is getting added only the relevant data gets added it's not like the whole image is going into the blockchain one but only probably the hash of the image and certain properties uh could be classification the label date time uh it was recorded etc so it's only the minimal amount of data that is going to the blockchain not each and everything yeah atul atul this is a ravish quick question when you say only the minimal data is going in the in the blockchain uh where are you in this architecture where are you storing the actual information is it still the hospital or is it in a centralized place yeah so that's a that's a good question so we we have actually our platform is very flexible so right now we have actually two alternatives one is the HPC cloud offered by various uh Indian Institute of Technologies the other is the couple of corporates have donated their uh aws and amazon space so it could be there also but uh looking at the architecture we really don't care as long as it is secured by their uh cloud security etc uh so we we manage very well the other aspects the access provenance uh and other things essentially if if there are five different organizations submitting that's a five different hospitals or different institutes submitting the information to the chain you are just getting the pointers but they are also saving all that information in in their own cloud or in their own infrastructure and giving you the pointers for that not very realistically i mean we we have identified specific storage areas so it's not that anybody is free to store anywhere uh so it has to come because this is all government controlled data so it is coming to government controlled storage areas only okay thank you yeah so it's not not with the hospitals they they send it to the specified areas yeah okay and also so uh also to add uh those points uh so what happens uh even the images are stored in a specific storage area which is secured we also do the verification because what we are doing we are storing the hash of that image along with the certain critical information on uh blockchain and every time there's a verification happens of that uh whenever the images or the recordings that exist so in this in this screen you see the architecture here so on the left side we have hospital on the right side we have a ai radiologist so this is this mainly for medical image analysis and the center we have a blockchain platform so hospitals are generating the images and those images are secured in a storage hbc or cloud server and whenever analysis has to be done by ai radiologist so ai radiologist they are also using uh some very uh specific uh cloud server uh uh server where they put the user uh they they put their ai uh ai algorithm on that and the file is transferred in a temporary file storage which is accessed by that ai engine and do the scanning and uh split the results and then those results are uploaded on a blockchain network so when we say this temporary file storage after the files uh after the results are stored on blockchain we immediately delete that uh file or that image which is used by the ai algorithm uh so because image has to be kept very secured so this is maintained only in the secured stories and that temporary file storage only for the ai engine to scan and do the analysis and the results which are split out by the ai algorithm they go to the blockchain network and again over time over there every time whenever uh uh any user whether from the hospital because hospital doctor has to analyze the results so they get access of that uh result uh and uh access the result also happens through verification and they when the patients doctors nurses the insurance company or even regulators if they need to access certain results uh they have to be uh on the platform using sign up and uh they can based once uh uh it is authorized by patients they can view the results or the records any questions architect yes hi this is mike mccoy i have a question about uh potential data duplication or image duplication issues let's just say you have the same patient with similar images at different hospitals how are you guys either combating and or solving for the issue is a part of the d id's that are that are hoping to aggregate those insights uh are there ways you're you're trying to solve this at all okay so i don't see there's any uh possibility of duplicate image because suppose one patient goes to one doctor or one hospital so that image the x-ray suppose let's talk about a simple case of x-ray x-ray is taken by that hospital which is uploaded on the secured storage area for analysis purpose so after that if the patient goes to a different doctor or different hospital then they will have to go for a different image and that it will be a new image and again analysis of that image has to be done again because the upload of the set to get that image would be done by the the hospital who's actually taking that x-ray or the CT scan so it cannot be done by the patient it has to be done by the hospital so there's no question of having a duplicate image so it's only one image at a time yeah so to add to what Naresh said we had some discussion about time series data because in reality a lot of times they use the image for day one day three day five and try to see the progression whether it is increasing decreasing etc but yeah so each of that will definitely create a different hash this is what our belief you can say is so as long as they have a different property or different property value which is hash we should be able to manage them as different versions or different ID etc yeah definitely different for different files yeah sorry go ahead sorry sorry you and you guys are taking the derived data sets you need an analyst to one are you taking this information at rest or is this a separate secured image storage that an analyst would have to upload to then you could be able to to do all your work moving forward yes first it has to come to the secured storage area then only it can be transferred because the radiologist who should use that and and that goes through a temporary file storage yeah but this is for the covid case I mean for tuberculosis there have been some age analytics in action but that's not in place right now for the covid scenario because of the sensitivity sensitivity privacy and security of those images right now hi this is jeff stolman I'm what it sounds like to me is that you basically have a system that uses data where you control access to the data but the blockchain is just being used to verify the integrity of the data by looking at the hash is that correct because otherwise the the raw data is being stored in these you know aws servers and it's accessed when somebody has the right to access it they make a copy of it oh that copy then gets destroyed but all that is kind of off blockchain the blockchain's merely verifying the hash in the integrity of the data yes yeah that's just one part of the puzzle because as Naresh explained there are DIDs so anybody trying to get to the images as I explained today they're already there we have seen some leakages and data flowing around so that will be completely controlled by blockchain so anybody wants to access look at the image will have to go through his DID generation process verified by proper authorities and he or she will or it will have uh the access based on their role like radiologist will have certain way to look at the images doctors will have a different way uh insurance companies will have a different way and patients will definitely so the credentials the credentials issued will be tracked the data that's used to authenticate and and and authorize someone to use the data will be stored on the blockchain as well and we even have a bigger goal like we even want to trace the lineage of the data where it traveled if at all it traveled how it traveled and the auditing cases as Naresh explained the who access for how long they're there we also want to plan a duration for the access so someone cannot access it infinitely but for specific time period etc so you're going to use a smart contract for that or something yeah just trying to avoid that word yeah okay thanks so it's not only verification as I mentioned so data protection and privacy and auditability so these are four different points I would say here data security data privacy auditability my tracking the transactions and also verification so I believe these are the four key pillars of the overall solution of course being a blockchain it's a trusted platform no record can be altered or deleted and it's quite secure any other question on this particular slide Naresh so there were some questions on the chat and I haven't tried to answer them in my capacity okay it sounds like you could delete data you just would still have a record of the hash of that data but if it's no longer there if someone deleted it it's deleted yeah so in that case suppose somebody deletes the data from secured stories if the image file is deleted in that case the verification cannot be at the time of verification will come to know that somebody has done something the action can be taken at that time and even if somebody somebody goes so the way it's going to work is if some image has somebody is trying to manipulate that on the cloud server so automatically the new hash will be created and whenever verification has to be done that verification will not happen it will fail and will come to know immediately that somebody has done something and at the time analysis can be done and action can be taken in order the logs themselves hashed or the logs just available to find out who was the one accessing it at the time when someone tried to modify the data yeah so the logs at this point are not hashed and they're not deleted but coming back to your earlier question we'll talk about it when we talk about compliances so if the HEPA says you cannot delete anything for seven years then so the amazon cloud for example has a provision where you can have s3 bucket that's what they call it where you don't have any deletion rights or you have only read permission so in that case your deletion case doesn't even apply yeah so that's that's what we're using here s3 bucket like all the images are stored or managed through s3 buckets and the logs are created over there every time with each change all right shall I proceed further yes okay so this is one slide which I want to talk about is for the record verification so we are using the self-sovereign identity so whether it's hospital or the patient or the doctor verify anybody he has to have a credentials on the blockchain and they have to be verified so if the record is created requires a digital signature from the user and even at the time for accessing the record it requires the verification of the signature and as I mentioned we are using hyperlidic fabric which is permissioned blockchain so we what we are trying to do here by having a DID or decentralized identifiers we're trying to give a complete control and the ownership of the records with the patient because the patient is the real owner of that so without his consent no record can be viewed by the by anybody in fact so that's what we're doing here so in terms of compliance is we are trying to comply with all international major standards whether we talk about worldwide can I add something to your earlier slide so this might be a little strange for people in the healthcare domain because usually patient comes to a hospital and he just forced to sign some form that you give a consent to sharing the data and hospital indirectly becomes the owner of the data so here we are trying to change that at least with the covid data which might be milestone or maybe a drastic change in the healthcare industry we hope this spreads all over and patient becomes the real owner of the data so that that may be the direction where this may be headed yeah yeah oh sorry could we go back to the previous slide yeah please hi for zero knowledge proofs can you go over the specific technology you're utilizing uh and or or how you are in creating that bridge between the patient to the the doctor or the verifier uh okay so here in this particular case first of all we are using half ledger fabric uh so we are not using indoor any other platform so we have written contracts smart contracts so that we are managing the whole thing so here the patient would have the wallet the application and whenever he creates he signs up we are creating a d i d for him on the blockchain and that d i d is of basically certain information basically that is a hash of certain information which he enters but we are not storing that information that his personal information you're not storing over there so the only thing what he is doing is creating the d i d with certain information and also when he signs up he enters certain parameters of physical health after that uh whenever he visits the doctor the doctor creates a record of his health parameters it could be his description or certain thing or lab reports and all that sorry so i just i just had a question on the type of zero knowledge proof technology you were utilizing for this i guess oh okay okay all right yeah fine all right so we are just using half ledger fabric for that okay okay all right thank you so in terms of clown compliance is i mentioned uh so we afford we are using d i d which covers w3c and uh if we are taking care of for HIPAA compliance is by uh doing data privacy data security audit control and access control and uh as we are using the the this uh self sovereign identity we are able to take care of for the right to share the right to delete so as such we are trying to cover all the major compliances uh while designing the solution and this particular slide talks about the blockchain architecture uh we have created a multi hosting architecture uh where uh it could be any cloud server so uh the multiple nodes uh and uh we are giving a node to each hospital also so hospital will have one node and each hospital is created one organization and they are free to choose any cloud network where they can have their node and they become the part of the overall network so there are few nodes so we have created the four organizations one organization is maintained by us and three organizations are for different regulators so because this is right now that is the kind of structure we created for our academic or educational platform the same structure we are targeting here to do that we will have one organization as part of that uh uh overall uh we're keeping one node and the three nodes the three organization will be different regulators so uh in terms of consensus so whoever is generating the data this hospital one organization five generating the data in that case they will participate in the consensus along with uh the regulators and the snapper nodes and uh we have defined certain criteria for uh endorsements and to and for the ordering so that uh we are able to maintain a proper consensus mechanism so this is the kind of uh and okay so in this case uh the hospitals the labs the government they are actually are the other data generator uh snapper and regulators they are mainly they're only for the governance so because the data is not uh us regulators are simply are there to make sure that uh uh the compliances are maintained so that's the blockchain architecture any question on this okay so I'll go to the last slide this is my last slide yeah so Naresh uh going back to the previous slide yeah so I think uh you need to point out the snapshot part of the architecture which is unique to snappers uh addition to the hyper laser generic architecture do you want to say what that snapshot really is yeah so as I mentioned the uh the the way we have architecture uh the whole solution here uh we are uh basically we are using hyper laser uh network but or using the hyper laser network how we have architecture that is mainly a using a combination of uh channels and multiple nodes on uh different cloud server uh that is the overall architecture but I'm not sure like what is the question you're trying to yeah so I mean the snaps snapshot part uh is basically the snappers addition on top of default what hyper laser mandates correct correct correct yeah so snapshot is an application which is built uh using the uh hyper laser fabric network and uh over there uh if you talk about on the application side we see because we need to maintain uh data privacy and the security uh over there uh the data is basically the responsibility of the data generator which are in this case the hospital of the labs right so third snapshot is basically a representation of data in a way right that is that is true that is true basically each record see uh so let me clarify that here uh and uh it just started mentioning uh snapshot is uh from uh snapper certificate it's it's derived from that so initially when we started this our intention was to go for education academic path later on the way whole solution was designed architecture and developed we found that uh the same thing can be used for uh different industry and here in this particular case the main thing is uh once the record is created even like health record is created for the patient it's permanent nature that doesn't change the only thing is the only thing is we need to verify that every time it should be secured it should be uh uh accessed with the consent so that's the main thing here so we are recording all the uh uh say it's like a certificate academic certificates when you're doing a degree a degree is created a certificate is created same way health record or any kind of health record yeah so i mean that is the only point i wanted was uh so you can create different verticals on top of your core architecture yeah correct education we have healthcare we have governance so that's very easy to do okay so i think we are running short of time you better move to the next yeah so this is the last slide actually uh most of the points are only covered it just was used yeah that's another question uh what consensus was used sorry yeah there's one question on the chat yeah we can take you are using wrapped uh wrapped right all right yeah you go with the slide okay so this is the last slide uh and in fact most of the points are only covered so what are the benefits we are getting so because uh uh data personal data of the patient we are maintaining of that uh using DID uh and all the health records are shared by the patient only with the consent of the patient uh and uh we are creating a connected ecosystems you are able to maintain uh data integrity throughout and uh data is secured and uh providence happens uh because we do the verification of the record every time and as you know that in blockchain uh the transactions the ledger are connections are immutable in nature and also they are cryptographically secured so auditability of the data is also being captured by us in the ledger and which which helps in uh regularity companses and uh uh data availability is there which can be verified at any point in time so it's uh uh it creates efficiency in the system too so any any question uh so I think uh we are almost there uh this couple of minutes the only question we can pick up those questions well excellent uh thank you so much uh excellent presentation uh just outstanding and uh clearly a good engagement with the with the with the team here the with the community here so thank you very much uh Naresh and um and a tool thank you very much yeah very much appreciated I'm gonna uh if I'm gonna take the uh take control back over if that's okay yeah please okay uh just to close out um so let me get back to the screen perfect we just have just a couple minutes left and so I wanted to just very quickly walk through resources uh this is uh part of sort of the big picture as a as it relates to those of us who are in the industry looking to to develop solutions much like what we just saw here and looking for funding so we maintain sort of an active list of funding support both globally and then here in the united states so I'll ask you to do a quick sort of walk through on these topics so we're not going to go do a deep dive on these but they are available and of course really at this point so much of the the COVID-19 resources are out there available and they're quite mature so if you have interest in continuing to develop solutions that relate to the COVID-19 pandemic please feel free to read through here I'll call out just very quickly some new information that came came about at the top of the really the top of the month the Robert Wood Johnson Foundation has two opportunities for engagement in the healthcare space not necessarily COVID specific but if you sort of read through it it's it talks through pandemic and how to sort of respond to that with that said I want to thank everyone again again thanks Nuresh and Atul I appreciate it very excellent presentation and again a quick thank you to Kamlesh for making introductions to get this in front of the HCCIG team with that said I think we're just about ready to adjourn our next meeting is in two weeks and in the interim have a great weekend and please be safe thank you so much yeah thanks a lot for giving us this opportunity absolutely yes thank you thank you thank you have a nice day bye-bye