To center the artificial intelligence and machine learning how to change the medical profession

nnWalking Comments: Artificial intelligence and machine learning are currently very concerned about the two major technologies, has great potential, many industries are seeking to apply to their own business to go. This paper analyzes the use of these technologies in this field from the perspective of medical treatment, analyzes the possible role of the project through specific project use cases, and portrays a more intelligent medical blueprint for people.n
nTranslated by: Inan
1. What is artificial intelligence and machine learning?n
These are the so-called 21st century technology.n
Artificial intelligence is the theory and development of a computer system that can perform tasks that usually require human intelligence (such as visual perception, speech recognition, decision making, and language translation).n
Machine learning uses algorithms to learn how to perform tasks such as prediction or classification without the need for explicit programming. In essence, the algorithm is not pre-specified by data learning.n
Machine learning and artificial intelligence have several levels, including:n
nSupervise learningn
Unsupervised learningn
In-depth studyn
nEach level requires a lot of data, and can be associated with human speed and accuracy to create relevant and available information. This is the role of artificial intelligence and machine learning.n
2. How will the center be applied to this?n
There are several benefits to centrality.n
The ability to achieve data privacy and create a collaborative atmosphere. To the center of artificial intelligence also have the same advantage. The machine learning model ensures data security and protects privacy. This is done by streaming back and forth and storing the data on the other end of the user’s device. In addition, once the model continues to learn and mature, they can be open to everyone in the network, allowing access. In this way, no longer need to focus on the proprietary organization. This is important because the central authority has the final say in the fate of the future.n
3. how does it work?n
Block chain technology enables interaction.n
These interactions are based on a set of agreed business rules. These rules can define payment transfers or smart contracts. A decentralized peer-to-peer network has these rules to validate the proposed transaction in a smart contract. This network can lay the foundation for the platform. Data aggregation and depth learning models can be developed, otherwise the cost of central institutions is too great.n
In this era of mobile phones and tablets, these devices are the primary computing device for many people. In view of today’s consumers are connected with their mobile devices, frequent user interaction and powerful sensors will appear, to achieve an unprecedented amount of data, which is often a private nature. The sensitivity of the data means that it is stored in a centralized platform with risk and responsibility. As a result, models with user data can greatly improve availability by driving smarter applications.n
4. How does this technique apply to medicine?n
There are many use cases.n
In the medical profession, there have been some projects to develop interesting products, such as Neuron. These products will guide the user how to train their centering artificial intelligence; in other words, how to train the trainer. Users will be able to see how to build their health data sets and how to access them.n
A module with computer visionn
This product uses artificial intelligence and machine learning to automatically fill in the user’s physical data on the app, just a self-timer can be. The Selfie2BMI module uses state-of-the-art deep neural networks and optimization techniques to predict various human characteristics, including height, weight, BMI, age and gender. It can also monitor 23 facial properties such as skin, hairline movements, wrinkles, teeth and other properties.n
Blood check decodern
This is another innovative use developed by Neuron to enrich blood knowledge as a deep dialogue agent, enabling users to discuss and answer any questions about blood biomarkers. It has learned thousands of medical documents and frequently asked questions to answer complex questions about blood test results. Agents can personalize conversations based on their age, gender, and condition.n
Genomics Detection Decodern
This deep dialogue agent aims to enrich the knowledge of genetic counseling, can answer the relevant simple and personalized complex issues. It can remember every visit and recommendation. When it can not answer, it will be from the large-scale data set to find the answer.n
Medical decodern
This module accepts instructions such as drug usage, side effects, etc. to answer individual questions. If genomic testing results are available, it will be linked to the pharmacogenomics recommendation engine.n
5. Why is this technology vital?n
This will make the medical experience more interactive and tailored to the user.n
Dealing with Artificial Intelligence can handle several key issues and provide users with the opportunity to regain control of their health care.n
These solutions can guide participants to find and collect their own medical data. Most people can not get their medical information, they do not know where to start, even if they start to find, their computer science knowledge is also very limited. These solutions also nurture and support open source developer communities to help them innovate tools on tool platform stacks, facilitate data integration and collection, and provide algorithms for interpreting data: centricization for personalized biology Kaggle.n
Fair datan
We can track and validate data sources through block chains. This allows accurate predictions, and can review the source of the data, perform data forensics, and Know your Data processes.n
The technology enables users to achieve safer health care. Some randomized trial data tends to focus, for example, these highly selective systems do not like to choose women, the elderly and those who have other medical conditions, pregnant women are basically ignored.n
Privacy issuesn
People may be hesitant to share their medical data on the web, because the network may lurk with malicious strangers. By distributing the data to all users, you can encrypt it so that it can not be changed. In addition, Neuron meets HIPAA requirements by maintaining edge devices rather than information on the cloud or centrally server.n
Future opportunitiesn
Although the health care industry can not create a doctor on the machine, but there is room for artificial intelligence to play a lot, and Neuron may become the leader in this field.n

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