Recently, Zuoshouyisheng, a leading domestic medical artificial intelligence system research and development company, announced the completion of a 100 million yuan B round of financing. This round of financing was led by Qiming Venture Capital, followed by Haier Capital and other well-known investment institutions. Yikai Capital acted as Zuoshouyisheng’s exclusive financial advisor in this transaction.
This round of financing will be used for the research and development upgrade of Zuoshouyisheng’s AI product pipeline and the expansion of related commercial application scenarios.
Founded in 2015, Zuoshouyisheng is an innovative enterprise focusing on the application of artificial intelligence technology in the medical and health field. The company integrates the latest AI technologies such as deep learning, big data processing, semantic understanding, and medical interactive dialogue with medicine, and is committed to Create “active medical AI”, use technical means to expand the supply of high-quality medical resources, and alleviate the contradiction between the excessive concentration of high-quality medical resources and the excessive dispersion of patient needs.
The company’s core product, the AI doctor platform, has covered more than 6000 common diseases in 35 main departments. By organically combining the underlying engine with different application scenarios, it provides listening and translation robots, intelligent online consultation, intelligent post-diagnosis management, and intelligent pharmaceutical affairs. Various solutions such as management, artificial intelligence Internet hospitals, etc., have currently served more than 500 industry customers, covering tertiary hospitals, insurance companies, multinational pharmaceutical companies, Internet giants, chain pharmacies, health management companies and other fields.
In terms of the underlying technology, Zuoshouyisheng has achieved a leap from “passive AI” to “active AI”. The AI learning model is no longer limited to a single drive of knowledge graphs, but is upgraded to a two-wheel drive of “data + knowledge”. Zuoshouyisheng hopes that AI doctors can follow the experts of the head hospital in a real diagnosis and treatment environment to dynamically learn the diagnosis and treatment logic. Under the “active AI” learning framework, there is no need to label too much training data, and only need to digitize and structure the doctor-patient interaction content in the real scene to support the efficient learning of AI.
In addition to the iterative upgrade of algorithms and models, the reason for helping the company realize this technological innovation also benefits from the innovation of data sources. The company launched the first domestic clinic listening and translation robot at the CHINC conference in August 2020, which has attracted widespread attention in the industry. With excellent hardware conditions and leading end-to-end voice processing technology, the device can be intelligent in a noisy clinic environment. Separate the doctor-patient dialogue, and then, with the support of the voice recognition model for professional terms in the medical field, accurately understand the content of the doctor-patient communication, and analyze and generate a structured electronic medical record. With the help of the interpretation robot in the clinic, doctors can generate standard medical records without second oral dictation, and support copying or import the electronic medical record system through the interface, which saves the time for doctors to “write” medical records, thereby improving the efficiency of consultation. In the process of assisting doctors in diagnosis and treatment, through the federal learning model, under the premise of ensuring the safety and confidentiality of hospital data, the listening and translation robot can independently learn the diagnosis and treatment experience of well-known experts in the head hospital. This is the “active type” advocated by Zuoshouyisheng. The essence of “AI” lies.
In terms of scenario applications, Zuoshouyisheng has created a set of anthropomorphic, full-skilled AI doctor diagnosis and treatment system that can serve various application scenarios. Based on the “active AI” learning method, AI doctors have changed the “formatted” rigid doctor-patient dialogue mode that was common in the past, and communicated freely with patients through flexible and anthropomorphic language, relying on massive medical knowledge and advanced Diagnosis and treatment experience, serving the entire scene of patients’ online and offline medical needs, and the entire process before, during and after diagnosis. It can cooperate with head hospitals in a SaaS model to serve the construction of smart hospitals and the operation of hospitals’ own Internet hospitals; cooperate with well-known pharmaceutical companies to serve the long-term tracking and management of terminal patients of pharmaceutical companies, and provide real-time data feedback and medicine Support and combine product networks to achieve drug promotion; cooperate with Internet giants to serve online diagnosis and treatment, improve the conversion rate and activity of patients’ online consultations, improve user experience, and increase payment stickiness; and insurance companies, health management companies, chain pharmacies Cooperation, serving long-term health management and chronic disease management of private domain traffic such as policyholders, employees, and members, and helping to build a user welfare system.
Zhang Chao, founder and CEO of Zuoshouyisheng, said: “Thanks to the new and existing shareholders for their trust and support to Zuoshouyisheng. The Zuoshouyisheng team will continue to adhere to the mission of’creating active AI and making high-quality medical care within reach.’ Service efficiency and improve patient experience. Zuoshouyisheng continues to provide the industry with an “online and offline integrated medical service engine covering pre-diagnosis, in-diagnosis, and post-diagnosis”, and at the same time, cooperates with the top three hospitals to provide patients with post-diagnosis in the Internet hospital model Manage services, ease the pressure of offline medical services in hospitals, and help patients with home rehabilitation management.”