Forbes Healthcare Report: Blockchain will transform from hype to commercial value in the coming year

According to Forbes’s latest “Eight Healthcare Forecasts for 2019”, the blockchain will transform from hype to commercial value in the next year. It is expected that by the end of 2019, 5%-10% of healthcare blockchain applications will be embraced in the pilot phase Limited commercial availability, and companies such as Change Healthcare, Hash Health and […]

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Number Button Technology: Make efforts on the “blockchain + medical” track to realize the interconnection of medical data

The eleventh white paper “Medical + Blockchain: Application Reform in Multiple Fields” issued by the Zhejiang Digital Medical and Health Technology Research Institute pointed out that “Medical + Blockchain had application cases in 2014. With the basic technology, the bottom layer With the maturity of the chain, the number of industrialized applications has begun to

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What changes will the blockchain bring to the medical field?

Blockchain is a new application mode of computer technology such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm. The essence is a decentralized database, and some people say it is a distributed public ledger. Everyone can update this ledger, but it cannot be tampered with. The so-called centralization is a center that

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Ten Application Scenarios of 5G Smart Healthcare

It is said that 5G will change thousands of industries. Among them, 5G healthcare is an important application field of 5G technology in the healthcare industry. With the arrival of the official commercialization of 5G and the full integration and application of cutting-edge technologies such as big data, Internet+, artificial intelligence, and blockchain, 5G healthcare

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Several integration points between AI products and the medical industry

1. Medical imaging At present, more than 90% of medical data comes from medical imaging. Medical imaging data has become one of the “evidences” necessary for doctors to diagnose, and it is also an important basis for cancer diagnosis. Take lung cancer as an example: In China, a tertiary hospital receives an average of about

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Waiting in line for three hours and seeing a doctor for three minutes, can AI help?

According to survey data from the Ministry of Health, nearly half of China’s residents do not seek medical treatment when they are sick. “Queue for three hours and see a doctor for three minutes”, I believe that many patients have experienced the dilemma of “three longs and one short” (long for registration, waiting, and taking

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From the current AI crown to the future value revaluation: Decoding the Ping An Medical Ecosystem

In 2016, the Central Committee of the Communist Party of China and the State Council issued the “Healthy China 2030” Planning Outline for the first time, which proposed that the scale of the medical service industry should reach 16 trillion yuan by 2030. The realization of this goal requires not only the expansion of “scale

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Artificial Intelligence: How far is the distance from the laboratory to the hospital?

Mike Barlow has this view in “Artificial Intelligence and Medicine”: Unlike traditional healthcare, which tends to be labor-intensive, emerging healthcare models are knowledge-driven and data-intensive. Many new types of healthcare are bringing us a new model that will rely on a new generation of user-friendly, real-time big data analysis and artificial intelligence and machine learning

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AI medical scenario business: How to use AI technology to identify and assist in diagnosis of esophageal cancer?

Video-assisted diagnosis mainly does two things: 1. Medical knowledge map construction; 2. Diagnosis based on disease. Today we will analyze how to use AI technology to identify and assist in the diagnosis of esophageal cancer. Esophageal cancer is one of the five major malignant tumors in the world, and my country is also a high-incidence

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Specialized medical artificial intelligence platform: driving medical AI from experiment to application

With the continuous in-depth development of artificial intelligence technology, professional medical artificial intelligence platforms have gradually emerged. It is recommended to choose a professional integrated platform to save the work of platform construction and debugging and focus more on model training and system application. At the same time, the developed artificial intelligence system also has

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