Palo Alto-based artificial intelligence startup Doc.ai has announced the US launch of its blockchain-based conversational AI platform on Thursday.
Founded mid-last year by husband and wife team Walter and Sam De Brouwer, Doc.ai's technology allows healthcare organisations to offer their patients a mobile "robo-doctor" to discuss their health at any time of the day.
Doc.ai uses an edge-learning network -- which performs deep learning computations at the edge of the network or on a mobile device -- to develop insights based on personal data, such as pathology results.
Once the user provides access to health records, wearable device data, and/or social media accounts, the AI is then able to process the information and start drawing inferences between the datasets. Where relevant, the AI will ask the user for additional information -- such as what vaccinations they have had, or what medications they take.
According to Doc.ai, patients can ask questions such as, "What should be my optimal ferritin value based on my iron storage deficiency?", "How can I decrease my cholesterol in the next 3 weeks?", or "Why was my glucose level over 100 and a week later it is at 93?" and receive responses in natural language.
Walter, whose expertise lies in computational linguistics, explained the process to ZDNet: "So your blood results come in, and the machine says something like, 'Okay, let me go over it, I see your cholesterol, there's nothing to worry about there. Your triglycerides are good. I do see there is a little ferritin problem in the sense that your genome tests indicated that you have an iron deficiency, and so that means that your ferritin should not be within the normal range from 100 to 300. It should be optimal at 30, and it is 150, so we have to monitor that. Your glucose is okay, but it's pretty close to the borderline, at 99, so we have to monitor that too'."
"You can then ask, 'What can I do for my glucose?' and the machine will say, 'You can increase activity, you can sleep more, but I don't know what you ate yesterday'. Before you know it, you have a complete conversation with that AI, but you also train it. So next time you have a blood test, it has a memory [of your last results]."
When asked whether patients would be equipped with the medical knowledge to ask the right questions, Walter explained that the AI preempts the questions the patient is looking to derive answers for -- similar to how Google preempts questions as the user types in the search box or URL bar.
"While people are looking at their [blood test] results, underneath they see all the questions they can ask, and they cannot come up with any question that the machine does not predict because so many people before have asked it," the CEO said.
Walter believes Doc.ai addresses a number of problems, the first of which is the shortage of more than 7 million healthcare professionals worldwide, according to the World Health Organization.
"The problem is that there are not enough carbon-based doctors, so these doctors ... their time is taken up by filling in reports or educating us or trying to find our records and all the things they shouldn't do," Walter said. "They should do what they're trained for -- that is give us a point of view on what we should do and not all the bureaucracy around it."
"Because of the shortage, the access to human doctors is becoming more and more expensive. If you do genetic counselling, out of pocket it will cost $200, and if you just do it via telehealth ... that will probably cost you less than $100 for 20 minutes ... with our silicon doctors, it will cost you $1 a year for unlimited visits, so the disruption is really in the price point."
Walter, who relocated from Belgium to California in 2011, added that the best way to address the shortage of healthcare professionals and rising healthcare costs is to empower the consumer to take a proactive, rather than reactive, approach to their health. As such, Doc.ai is intended for preventative healthcare, rather than for the ongoing management of complex and chronic illnesses.
On why the company chose to use blockchain, Walter said AI needs to be decentralised.
"If we leave it as it is now, a couple of companies will basically own all the artificial intelligence. We have to decentralise it to the edge device -- that is the phone, it can be a laptop, whatever is at the edge ... [people] used to use their data and now they want to own their data," he said.
"The next thing is P2P, make it so that the nodes connect with each other, and then you have human blockchain."
The company -- which raised an undisclosed amount of seed capital from Comet Labs, F50, Legend Star, and S2 Capital -- has announced Deloitte Life Sciences and Healthcare (LSH) as its first beta customer and distribution partner.
Deloitte LSH is currently testing Doc.ai's Robo-Hematology solution, which was unveiled on July 24, 2017 at Deloitte University in Dallas, Texas.
Over the coming 12 months, Doc.ai expects to roll out three natural language processing modules -- Robo-Genomics, Robo-Hematology, and Robo-Anatomics -- to medical providers and payors. Walter said that in the future, there could be modules such as Robo-Metabolomics and Robo-Microbiomics, but admitted that the disciplines need to advance further before the startup can look into them.
While there are typical startup challenges ahead, Walter said Doc.ai's platform will become more and more relevant as health becomes "increasingly quantified". He agreed that numbers, in and of itself, can be difficult to understand, but explained that there will be layers on top of the numbers to help people navigate it better.
"You won't see the numbers anymore ... In the beginning of the internet, the addresses were just numbers. The first three numbers [represented] the country and now it's all .com; we just put layers on top of it," Walter said.
He admitted that Doc.ai's close relationship with Stanford University's computer science department will be advantageous moving forward.