AI and Healthcare Big Data Usher in Mobile Health 2.0: Jofon Medical Files for IPO

On the afternoon of March 10 (Beijing Time), the second match between Google’s artificial intelligence AlphaGo and South Korean Go player Lee Sedol concluded, with AlphaGo securing another victory. The realm of Go, once a source of human pride, now appears to have been conquered by artificial intelligence. This historic moment may signal that AI technology has entered a new era.

In the healthcare sector, the integration of artificial intelligence and medical big data is emerging as a new hotbed. A prime example is IBM’s robotic doctor, “Watson.”

In China, there is also a company leveraging artificial intelligence and medical big data for intelligent diagnosis: Jiufeng Medical. Wu Wenhui, founder and CEO of Jiufeng Medical, believes that the integration of AI and big data will usher mobile healthcare into the 2.0 era.

Wu Wenhui stated that the 1.0 era of mobile healthcare has effectively leveraged mobile internet technologies to enhance the connectivity of medical services. However, another resource of the mobile internet—medical big data—was not developed or utilized during the 1.0 era. The mission of the 2.0 era is to harness internet technologies to enable patients to contribute data, thereby improving healthcare quality and fostering collaborative governance between doctors and patients.

What Is Mobile Health 2.0?

In Wu Wenhui’s view, the development of mobile healthcare can be divided into three stages, which he refers to as the 1.0, 2.0, and 3.0 eras of mobile healthcare.

“Currently, most mobile health projects are still in the 1.0 stage,” said Wu Wenhui. Mobile health initiatives at this stage address the issue of healthcare accessibility, such as appointment registration, payment, and consultations via mobile internet, with their value lying in enhancing convenience. Such companies will ultimately follow a trajectory similar to that of web portals, where a few dominant players emerge. Many issues remain unresolved in the 1.0 era.

Wu Wenhui told VCBeat that the e-commerce model cannot be simply replicated and applied in the mobile healthcare sector. “Medical products differ from those in traditional e-commerce. In the traditional e-commerce space, if a user needs a cup and the platform’s integrity is sound, the value of a cup of the same brand and model is equivalent to that sold in high-end offline malls. However, purchasing via e-commerce offers greater convenience and price advantages.” Wu Wenhui stated that current medical quality cannot be standardized, and the varying levels of medical service make it impossible to achieve large-scale online healthcare.

“This means that app models simply pursuing doctor and patient traffic are insufficient, as is basic big data. The development of big data must incorporate artificial intelligence; only by leveraging big data and AI to assist physicians in diagnosis and treatment can we align with the future direction of the Mobile Health 2.0 era.”

“In fact, leveraging AI and big data to assist physicians in diagnosis is both practical and valuable. It can help doctors reduce diagnostic risks and improve the quality of care,” Wu Wenhui told VCBeat.

In Phase 3.0, the primary objective of mobile health is to reduce overall costs while ensuring the quality of medical services. The cost reduction mentioned by Wu Wenhui does not merely refer to the simplistic approach of “selling drugs online to eliminate intermediaries and lower prices.” Rather, it aims to provide patients with accurate diagnoses and the most appropriate treatment plans, thereby reducing their total economic burden caused by factors such as misdiagnosis and inappropriate treatment.

How Should the Application of Artificial Intelligence + Big Data Be Implemented?

Due to the lack of high-quality big data on diseases, the progress of "AI + Big Data" in China is currently not rapid.

Amidst this broader landscape, Zhongke Jiufeng Medical’s big data-driven precision medicine software platform is being implemented in primary care hospitals. It is understood that Jiufeng Medical’s current core software offerings include: an AI-powered imaging diagnostic system for lung cancer; an AI-enabled structured reporting tool for lung cancer, which leverages evidence-based medicine to automatically identify pathological findings; and a lung cancer treatment planning system that utilizes big data and artificial intelligence to generate personalized treatment regimens. Notably, one of its AI imaging software products, developed through international collaboration, has received clearance from the U.S. Food and Drug Administration (FDA).

Jiufeng's model is to establish a "iron triangle" cooperation mode:

In the medical field, we collaborate with top-tier domestic and international healthcare institutions, such as Harvard Medical School, Peking Union Medical College Hospital, and Changzheng Hospital.

Collaborate with the Chinese Academy of Sciences on information technology processing.

Collaborating with leading international technology companies in medical imaging.

Currently, Jiufeng Medical has partnered with the Chinese Academy of Sciences’ (CAS) State Key Laboratory of Molecular Imaging to participate in the CAS Science and Technology Service Network (STS) project—“Regional Telemedicine Collaborative Imaging Diagnosis Science and Technology Service Network”—led by Professor Tian Jie, a renowned domestic and international expert in radiomics. Through this collaboration, the Institute of Mobile Healthcare and Molecular Imaging Applications (Nanchang) under the Chinese Academy of Sciences was established. Joint diagnostic analyses based on imaging data from 10,000 lung cancer patients have achieved internationally leading standards.

In China, how can artificial intelligence be successfully applied to healthcare? Wu Wenhui believes there are three key points:

First, how can we sustainably, legally, and cost-effectively acquire in-depth medical data?

Second, how to transform the acquired data into relevant medical knowledge for diagnosis?

Third, what are the application scenarios for medical knowledge derived from big data?

“Jiufeng is on a path of exploration, and we hope more like-minded individuals will join us in blazing new trails,” said Wu Wenhui.

Team Introduction

It is reported that Zhongke Jiufeng Medical secured investment from the renowned Taishan Investment and US-based Greybird Fund during its angel round.

Jiufeng Medical boasts a world-class core team, led by its founder and CEO, Wu Wenhui, the former President of Siemens Healthineers for Northeast Asia.

The company’s COO, Wang Tongyan (co-founder), is the former Vice President of Janssen Pharmaceuticals, a Johnson & Johnson company, and former Vice President of the China Association of Pharmaceutical Commerce.

Tom Miller, an investor in Jiufeng Medical, is the founder of the first precision medicine fund in the United States and a renowned national leader in medical innovation thought leadership.

Tom Miller stated that “Jiufeng Medical” is, in essence, a remote “precision medicine” initiative. With internet healthcare being his longstanding area of interest, he hopes that more technology companies and capital institutions will join forces to drive the development of Mobile Healthcare 2.0, thereby extending the benefits of advanced technologies to a broader population of patients at the primary care level.

Text | Zheng Qi, Zhang Caixia