doc.ai, a new startup aiming to disrupt the healthcare sector, came out of stealth mode last month and has raised approximately $2.3 million in its token pre-sale.



The startup is creating an advanced natural language dialog system that generates insights from combined medical data. It recently announced the launch of its advanced natural language processing technology platform using the blockchain to timestamp its datasets and decentralize artificial intelligence.



doc.ai plans to roll out three natural language processing modules over the course of next 12 months. This includes Robo-Genomics, Robo-Hematology, and Robo-Anatomics. Of these, Robo-Hematology was unveiled on July 24, 2017 at Deloitte University in Dallas, Texas. doc.ai is working with Deloitte Life Sciences and Healthcare to test this solution.



Founder Walter De Brouwer is a strong believer in the blockchain technology. In a blog post titled “The Summer of Coin”, he wrote:



“The crowd is slowly sapping power from the state. It has started with the two main prerogatives of the state: real estate and money. Ethereum created its own virtual real estate, there is a decentralized Silicon Valley buzzing in our everyday reality now, a permissionless, decentralized new dimension where transparency and code rules; and we all know about Bitcoin and ETH…The next 3 prerogatives state disintermediation are coming in new ICOs this very summer: stateless identity guaranteed by code (the CIVIC ICO already happened), to be followed by decentralized Healthcare and Education ICOs.”



Speaking to EconoTimes, Walter De Brouwer discussed the inception of the startup, the journey so far, and future plans:



ET: How was the intersection of blockchain and AI for healthcare sector conceptualized?



WB: I had dinner in La Jolla, CA early 2016 with a good friend, Eric Topol MD, the author of “The Patient Will See you Now”. We talked about bottom-up medicine and he convinced me to look at the Blockchain and medicine. I was already a believer in Bitcoin and blockchain technology, I just had not put the two together. The next day I started to think about how this could be done. I quickly found the convergence: AI for medicine and the Blockchain for decentralization and logging dataset coordinates to prove provenance would be the way to verify ownership and to start a new economy where what you invest in your health becomes a financial asset – forking healthcare.



ET: It has been a year that doc.ai was founded. How would you describe the journey so far?



WB: We set up in August 2016 in downtown Palo Alto, CA and much of that location actually determined the company. Close to Stanford, our teams came right out of university into often their first job. They had all met in one course during their Computer Science curriculum, CS 224d (deep learning and natural language). Six months later we had our first alpha’s running and signed a distribution license with Deloitte. Three months later we decided to combine AI, healthcare and the blockchain and started preparation for the ICO. We are now in the middle of it. It is the greatest adventure of our lives to date: the public invests money in us to set up a public infrastructure, a parallel stateless network where everyone in the world can train their own medical AI. It is just fascinating to think what this venture could be 10 years from now. Will it change a buyer’s market into a seller’s market? Will it win battles against idiopathic diseases (when the doctor says “I do not know what you have but it is not good”)? Will developers all over the world branch off our Github and make their local versions? Will older people enjoy an extra income just by selling their health data? The potential just depends on your imagination.



ET: Would you like to tell us more about Robo-Hematology and the collaboration with Deloitte Life Sciences and Healthcare?



WB: The future of diagnostics is going inside the body as anything you can measure on the outside is crude, noisy and full of bias. The best medical data comes from inside of the body, for example bodily fluids of which blood has been the most studied. It is a fluid that bathes all organs so collects data from each of them. Blood results are ideal for robo-health: they are a vertical domain of some 800 biomarkers with regulated ranges, and the causal relationships between them are well understood. Much time, money and efficiency is lost by having doctors read the results and then communicate them to patients. It is a part of the industry ripe for disintermediation. Blood results come from the lab and you can talk to the results and ask them questions and for some sensitive values (less than 0.01% of the cases), the carbon-based doctor takes over. The machine is the ideal triage and educational component.



From the beginning doc.ai was set up as a highly-skilled engineering outfit. We do not have a salesforce to be able to go into long negotiations with large healthcare providers; we are not able to implement our source codes into their organization, there are only 16 of us. Therefore, Deloitte was the ideal partner, the biggest healthcare players are already their clients and we need big players because our neural nets need lots of data to train.



ET: What are the planned next steps following the ICO?



WB: We see the reinvention of healthcare as a neo-darwinist process. Entities are rewarded with survival because of 3 things: they collect information about their environment, they use this information to anticipate the threats and rewards that will come at them, and they act upon it immediately.



For the NEURON Network this means three stages: collection, prediction and action.



Without collection of data about the environment no prediction of action can happen and that is what we are going to do the next six months before we open the network. Finishing the AI toolkit to collect the information about people’s environment in such a way that they a uniform and normalized quantified biological profile. We are putting so many layers on the AI so that it will seem a frictionless and entertaining onboarding of all that data. Once they start collecting, our community of data scientists will be ready to work on their data with predictive models. Once they get the model, they can choose to change their behavior. The future of data science will be behavioral science.



"It is not the Strongest species that survive, nor the most Intelligent, but the ones most Responsive To Change" - Charles Darwin, On the Origin of Species 1859



Upcoming Token Sale



In order to power its platform and incentivize the community, doc.ai will create ERC-20 based digital tokens, named Neurons (NRNs). doc.ai will sell and issue Simple Agreements for Future Tokens (SAFTs), which will convert into NRNs upon the launch of the platform.



The crowdsale process will kick off on September 28, 2017. According to the terms of the token sale, a total of 860 million NRN will be created, with one NRN representing 100 neurons in the human brain. Approximately 37% of the total number of NRNs is expected to be sold in the SAFT offering.