Helios Neural Network been one of the exciting cryptocurrency project in 2018 is a platform design and proposed with the purpose of uplifting the cost and compute payload into a distributed network via a custom built Blockchain comprised of master nodes. The master nodes will be rewarded for storage and compute proportional to the contribution made into the network. Globally, healthcare providers of diagnostic imaging and other medical modalities will be able to send data into the HNN network using industry standard protocols with the assurance that the data will be preserved for use in the betterment of care via Ai solutions. Using this approach, the HNN network will not only provide computing power for researchers and Ai applications but also allow access to low cost unlimited distributed storage that is catalogued, immutable, secure and anonymised. Ai vendors, through compliance will be able to send their existing data into HNN providing an immediate cost saving on infrastructure. Many Ai vendors are currently partnered with healthcare providers for data access; HNN will provide means to leverage these partnerships with defined smart contracts ensuring any stipulations for restrictions on data access are upheld where applicable. Through the use of custom APIS that comply with industry standard protocols such as DICOM and FHIR, HNN will enable integration with existing clinical record and acquisition systems for seamless commits of data into the network. To ensure transparency, the network will be able to be queried for as-is state at any point and will be able to return results from SQL-type queries that comply with bespoke requirements and contract criteria. This approach will ensure that the confidentiality of any stored data is upheld to the highest level possible. Helios and Health Helios will connect with health care department with the approach and method of Helios Health i.e. Health industry specific Helios Connect application that natively support anonymization of data, integration with existing IHE standards such as Dicom and HL7. XDS will be added in a later version. Helios Health Connect can act as Dicom Service Class Provider (SCP) to receive Dicom images. When images are sent to the Helios Health Connect SCP the Dicom header is read, with all identifying data removed, data is temporarily stored in a local cache until the report has been received via HL7. The relevant information is added to the image/s manifest ready to be stored and processed on the Helios Neural Network. Once storage has been confirmed on the Helios Neural Network the data will be removed from the local cache. To retrieve data from the Helios Neural network a dataset is built from the subscribed data within the Helios Health Connect application. At this point the data will be retrieved to the local cache where Helios Health Connect will act as a Dicom Service Class User (SCU) and send the data to the receiving application. In parallel the relevant report data will be used to generate an Observation Result (ORU) HL7 message to provide context to the Dicom images being received. Road Map July 2018 Private Presale end, Public Sale Begins August 2018 Public Sale Ends October 2018 1st Partnership Announcement December 2018 HNN Testnet Launch January 2019 Helios Connect Testnet Dicom Support March 2019 Helios Connect Testnet HL7 integration added June 2019 HNN Mainnet Launch Helios Neural Network team Whitepaper Helios Neural Network Read more about the Helios Neural Network whitepaper Click here. Links Website. Medium. Facebook. Instagram. LinkedIn. Community Telegram. Bitcoin Talk.