MedAI Network — Medical Imaging on the Blockchain

MedAI Network
Feb 21, 2018 · 7 min read

Introduction

Over the past decade, there has been an incredible push in the health care ecosystem to improve care, reduce costs and create more efficiency. The healthcare IT realm has driven the majority of these pursuits from legislative changes through the HiTECH act through engineering advances in computer applications. In the past several years, we have seen the introduction and proliferation of two revolutionary technologies: blockchain and artificial intelligence. Traditionally, medicine and healthcare has been a late adopter of new technologies. This has served the specialty well in some cases allowing a new technology to be vetted before implementing in a high stakes environment where lives can be hurt. These new technologies, however, are showing to be notable exceptions.

Blockchain

The blockchain is a digitized, decentralized, public ledger of transactions. The blockchain is constantly growing as ‘completed’ blocks (the most recent transactions) are recorded and added in chronological order. The system allows market participants to keep track of digital transactions without central recordkeeping. Each node (typically a computer system connected to the network) gets a copy of the blockchain, which is automatically downloaded.

The underlying technology of the blockchain was originally developed as the accounting method used by Bitcoin, a digital currency, which uses what is known as distributed ledger technology (DLT). Currently, the technology is primarily used to verify transactions within digital currencies, but alternate applications are effective and possible. The technology allows data to be digitized, coded and inserted into any document into the blockchain. The application of the technology creates a secure record that cannot be changed. In addition, the authenticity of the record can be verified by the entire community using the blockchain instead of a single centralized authority.

Developers have begun deploying the blockchain technology across numerous disciplines including fintech, government, internet and now healthcare. The ability to provide a distributed, secure ledger has multiple applications in the fields of telemedicine, electronic medical record and artificial intelligence

Artificial Intelligence

Medicine has seen an explosive growth in imaging across multiple disciplines including Radiology, Dermatology, Ophthalmology and Pathology. As these specialties grow, there is a natural increasing need for more quantitative parameters (biomarkers) in the care of the patient. The ability to implement these evaluations to medical imaging is well suited due to the data driven nature of this analysis method. The methodologies in some segments, however, are approaching the limits of human interpretation. The ability to create man-machine symbiosis in an initial phase with a long term evolution to complete computer based evaluation is the current driving force of the environment. The benefits of computer based interpretation as both an adjunct to the human evaluation as well as for more quantitative tasks is significant. There is a desire to both reduce the human error rate as well as the introduction of novel findings not humanly possible. The reduction in error is important in current health care system as error is often cited as the third leading cause of morbidity and mortality after cardiovascular disease and cancer.

Recently, artificial intelligence with the advancements in deep neural networks have allowed the progression of computer vision to approach and in some cases surpass human capabilities in complex image based recognition tasks. The current iteration of computer aided diagnosis (CAD) involves machines doing image analysis and identifying potential abnormalities in images (for example, lung nodule on an X-Ray study) for the physician (Radiologist). However, during the past five years, we have seen the advent of machine learning and deep learning with convolutional neural nets and other sophisticated algorithms that are pushing past CAD and now providing insights that go beyond human capabilities. This is seen, for example, in the ability of algorithms to predict the probability of breast cancer on a mammogram.

Enter the MedAI Network

Over the next several decades, there is an expectation that there will be a significant shortage of physicians. At the same time, we are seeing an exponential increase in the amount of medical data being generated around each patient. Each of these data points are relevant in the care of the patient both from the vantage point of diagnostics, but also treatment. Although medical care remains largely local and person to person, the advent of Telemedicine has grown logarithmically as there are multiple applications where it provides optimal care. Where we have seen the largest segment of growth has been in diagnostic medical specialties where the currency is imaging. These are specialties that provide evaluation of a patient’s condition via imaging such as Radiology, Dermatology, Opthalmology and Pathology and are well suited for transmission across networks. The teleradiology marketplace has matured with various iterations of provisions of care initially driven by cheaper cost by trying to provide off-shore work to time shifting and providing 24/7 coverage. These networks have now shifted to utilizing telemedicine networks more to improve care by providing subspecialty care by subspecialty physicians rather than simple economic factors.

The internet has matured to enabling patients to seek online consultations at their convenience from a geographic and timing perspective. The advent of over-the-counter tests to analyse your blood, sequence your genome or check on the bacteria in your gut is shifting the ability to obtain care into the patient’s hands. The development of technology is causing a shift. The growth of various technologies such as the smartphone and wearables are allowing patients to monitor and treat their own health. These technologies if coupled with access to your own medical records and the ability to share this information with those you trust amplifies and exponentially increases empowerment of the patient and provider and is a driver of the growth of Telemedicine. Technology allows a patient to reduce inefficiencies in their treatment and as a side benefit provides data to help train medical algorithms in the ecosystem at large.

Although health records and imaging are evolving to being electronic, they are still generally inaccessible and trapped. In addition, most health records are in a format that machines cannot read. The MedAI network empowers the distribution of these health care data points to the benefit of the patient, the physician as well as the network at large. The network enables these constituents to harness the full potential of future AI technology to, for example, provide automated medical evaluation and diagnosis.

The MedAI Network is a full service platform provider for telemedicine on the blockchain that supports multiple applications and inputs and allows the execution of novel technologies on medical data, namely AI. Our platform, unlike any other, permits and supports the transfer, transmission, storage, interpretation, second opinion, and evaluation by artificial intelligence of medical data and medical images across all subtherapeutic areas and medical specialties. The MedAI network is not limited to one medical specialty or subspecialty. The network can support any remote consultation between patient, physician, institution or sponsor.

This technology will be revolutionary in both providing decentralized storage and repository for medical imaging data, but will allows the application of novel technologies such as AI. While the network can support textual based EMR data, the MedAI network focuses on imaging data given that all providers of imaging based services share a common protocol (DICOM) and already move images around on networks and PACS. The deployment of AI and Deep Learning to these images becomes available despite not being locally available. The ability for the MedAI network to deploy these algorithms upon request across the entire network in real time at a patient or provider’s request opens AI to the entire planet. The core technology behind the network deploys a storage layer above an API layer using the blockchain. Developers all over the planet are able to develop decentralized apps that access the network and use the MedAI coin as the currency for interaction and exchange.

The MedAI network was developed to help three key constituents of the healthcare system. First, the MedAI network enables patients to access both novel and subspecialized therapeutic care across all medical disciplines that may not be locally available as it only exists in tertiary care centers of excellence. Second, physicians have access to larger groups of patients to be able to provide specific subspecialty and diagnostic expertise they may possess in specific medical conditions. Lastly the network supports sponsors performing clinical trials. The clinical trial app can securely transmit and store images being performed as part of a clinical trial through the storage layer on the blockchain from an acquisition site to an imaging contract research organization. This data then can become accessible to researchers to enable the development of new therapeutics.

In Conclusion

The recent advances in blockchain technology and AI present an intersection that is poised to change the healthcare landscape. As the implementation of both these technologies deploys into the healthcare ecosystem, the delivery, quality and cost of healthcare will improve to the benefit of patients across the globe.

MedAI Network

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AI Enabled Medical Image Storage and Telemedicine Platform

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