학술논문

Converging Blockchain and Artificial-Intelligence Towards Healthcare: A Decentralized-Private and Intelligence Health Record System
Document Type
Conference
Source
2022 2nd International Conference on Intelligent Technologies (CONIT) Intelligent Technologies (CONIT), 2022 2nd International Conference on. :1-8 Jun, 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Training
Support vector machines
Medical services
Machine learning
Predictive models
Decentralized applications
Data models
Decentralized Application (DAPP)
Artificial Intelligence (AI)
Machine Learning (ML)
InterPlanetary File System (IPFS)
Electronic Health Record (EHR)
Application Program Interface (API)
Proof Of Work (PoW)
Artificial Neural Network (ANN)
Support Vector Machine (SVM)
Natural language processing (NLP)
Latent Dirichlet Allocation (LDA)
Language
Abstract
In the current healthcare environment, they lock the patient records in multiple centralized systems which are maintained by the different healthcare institutions. So, the complete, comprehensive medical data history of the patient is locked away, making it difficult for doctors to make informed decisions. Our system aims at tackling these issues using a decentralized system to store the patient's record. The patient and the doctor/healthcare institutions use a Decentralized Application as an interface to the Blockchain network. When a patient visits the doctor, the patient can give access to his/her medical data through this Decentralized Application via an Ethereum smart contract. Once the patient gives access, the doctor can access all the patient's medical records and history in one unified interface. Artificial Intelligence and Machine Learning are used to give a tailored medical experience to the patients. With rich data that is available from the users' network, can be fed into the Machine Learning models to do various levels of analysis to give patients and doctors further insight into the medical records.