We often say that the true value of AI lies in empowering the grassroots. However, for AI companies, how to reach the grassroots is a question worth pondering.
Is there a model that not only allows primary care to enjoy high-quality medical services, but also enables artificial intelligence companies to find a reasonable model of access? Cloud platform might be one of the solutions.
In the recently concluded 2020CHINC, the “AI-assisted COVID-19 diagnosis -Cloud + AI Decisive Battle Against the Epidemic” project jointly completed by the First Affiliated Hospital of Chongqing Medical University, China Telecom, and Deepwise was selected among hundreds of projects across the country. It stood out from the crowd and won the third prize of the “National Selection of Outstanding Cases of Epidemic Prevention and Anti-epidemic in Medical Informatization”, and its core has solved the above two problems at the same time.
By relying on high-quality large-scale tertiary hospitals to establish a cloud platform, coupled with the massive equipment support given by China Telecom, low-latency, large-bandwidth 5G communication capabilities, Deepwiseis extending the boundaries of AI capabilities infinitely…
What Kind of Problems can “AI+Cloud” Solve?
As the name suggests, AI decisively defeats the “epidemic”. The origin of this project is this year’s anti-epidemic period. From past experience, there is an inseparable relationship between the outbreak of infectious diseases and the medical run during the epidemic. However, due to the development of communication technology and the limited medical resources, it was difficult for us to effectively intervene with this phenomenon.
So if we can set up the cloud platform to the cloud, put artificial intelligence in it, and then use the grafted medical consortium information platform, the National Health Commission can cover regional disease control and realize AI support with only a small investment.
Chen Liang, chief technician of the First Affiliated Hospital of Chongqing Medical University, believes, “In which case, patients do not need to travel to and from teritiary hospitals, and can complete inspection and diagnosis at the primary medical consortium that meets the requirements. This can effectively reduce the workload of the top-tier 3A hospitals and reduce the cross infections. Patients can receive information related to image diagnosis through mobile phones, which will effectively promote the construction of China’s proactive preventive public health prevention and control system.”
AI, 5G, and Cloud Work Together to Solve the Predicament of the Lack of Upstream Resources of the Medical Consortium
While the model may seem simple at the first sight, it must rely on a number of emerging technologies to achieve it.
The first is the 5G private network technology provided by China Telecom, which solves the problems of regional medical consortium connectivity and high-speed data transmission. In the past, one of the technical bottlenecks in the development of telemedicine was the insufficient bandwidth and excessive delay in the long-distance transmission process. The new generation of communication technology can bring a massive communication capacity of 1 million/km2, achieving a maximum of 10 Gbp/s. This means that remote video diagnosis and even remote surgery may become possible.
The second is the AI capabilities provided by Deeepwise. The AI technology employed by Deepwise not only enables decentralized medical system, but also effectively optimizes medical resources to tackle the shortage in medical resource in the current medial system.
During the epidemic, Deepwise developed a highly accurate and sensitive AI product to assist with diagnosis for COVID-19 in just two weeks, and logged into many hospitals in Wuhan within a short period of time, playing an important role in fighting against the epidemic. The cooperation with the First Affiliated Hospital of Chongqing Medical University focuses on regional medical screening and prevention capabilities. CT screening of patients in primary care can be quickly delivered to the top-tier 3A hospitals through the cloud platform. With the assistance of Deepwise AI, doctors can confirm the diagnosis results in just a few minutes. In addition, AI can also classify patients’ real-time status, give triage recommendations, help patients complete intelligent follow-up, and optimize the allocation of medical resource.
In addition, the cloud platform built by Deepwise has solved the problem of large investment in medical infrastructure. The platform seamlessly integrates cloud PACS, cloud RIS, cloud AI, cloud film and other applications. At the same time, it has the functions of remote diagnosis and high-definition audio-visual video consultation, realizing remote collaborative diagnosis and treatment.
At the same time, doctors can access this platform very conveniently. The platform adopts B/S architecture, no workstation is needed, and doctors can perform 3D image processing and application anytime, anywhere through the webpage. In practice, medical professionals can use computers, PADs, and mobile phones to quickly access the cloud PACS system at any time and any place, without having to go to a designated consultation room, to achieve remote MDT consultations, greatly reducing time costs.
Without a cloud platform, companies must install AI workstations in each institution and the financial pressure brought by them is rarely affordable by grassroots medical institutions. Therefore, through AI technologies and remote image review, Deepwise has created a shared space, making AI technology affordable for all primary healthcare.
In general, relying on cloud technology, artificial intelligence and 5G technology, the First Affiliated Hospital of Chongqing Medical University, China Telecom, and Deepwise are reshaping the public health prevention and control system of primary care under the medical consortium through technological changes.
Deepwise’s Trail Fighting Against the COVID-19
The COVID-19 prevention in “AI decisively fights the’epidemic'” is undoubtedly a good start. In fact, as long as we can implant sufficient and effective applications in the cloud, this model will be more abundant in the diagnosis and treatment process.
Li Chaoyang, senior vice president of Deepwise, told VC Beats,”Our core purpose is to help the medical consortium build a universal AI platform, like a mobile phone, on which hospitals can install apps with different functions. We hope to truly empower the grassroots medical institutions through this cloud platform and the employment of AI technology.”
Therefore, the construction of the cloud platform of the Medical Consortium of the First Affiliated Hospital of Chongqing Medical University set a good example. We also hope that such a model can be applied in more medical consortium and solve the medical impossible triangle problem through science and technology.