Embracing Healthcare New Infrastructure: XSmartAnalysis Launches One-Stop 'Clinical Research + AI' Cloud Platform

In recent years, the healthcare industry has been regarded as a key scenario for the practical application of artificial intelligence and big data technologies. With the continuous emergence of products such as intelligent auxiliary diagnosis, clinical prediction models, and AI-based medical image interpretation, the intensity of clinical research in these related fields has also been steadily increasing.

Furthermore, China has been advocating for the development of research-oriented hospitals. Scientific research output serves as one of the key performance indicators for such institutions, underscoring the critical importance and significance of clinical research.

However, at the outset of planning research projects, clinical practitioners in China often struggle not only with the necessary preparatory work—such as managing the substantial pressure from daily clinical duties, striving to carve out time for research, and securing research funding—but also with the lack of a user-friendly and effective research tool.

A study on the current status and influencing factors of research needs among in-service clinical medical and technical staff at a tertiary hospital in Beijing shows that,“Research Methods and Training” was the most selected option in the “Most Desired Support” category, accounting for 74%, followed by “Guaranteed Time” at 71.2%.

“Clinicians are extremely busy, and their core expertise lies in medicine. Even basic medical statistics present a significant barrier for clinicians, let alone data mining integrated with artificial intelligence. Yet scientific research is an essential requirement for physicians, which has given rise to a market for medical research data analysis. Within this market, some companies focus primarily on medical data integration, while we concentrate on clinical data analysis and modeling,” said Xu Yuan, founder of Jizhi Analysis.

The Jizhi Analytics Platform targets the clinical data analysis market by integrating over 100 analysis and modeling algorithms related to clinical research. It not only enables one-click execution of relevant analyses, thereby reducing the time researchers spend on coding and debugging, but also allows for one-click construction of clinical AI models, generation of research analysis reports, and creation of online prediction tools. This facilitates visualization of the analysis process and clinical prediction models, ultimately enhancing the efficiency of clinical research.

"Zero-based, one-click, and high efficiency are the main features of Extreme Intelligence Analysis."

According to Xu Yuan, in current clinical research, the high rate of misapplication of statistical methods is largely due to researchers’ lack of background in data analysis. Meanwhile, most traditional tools available on the market are user-unfriendly and often require custom coding, resulting in a steep learning curve.

In this regard,JiZhi Analytics integrates and optimizes over a hundred algorithms and models for clinical scientific research. After users upload structured or semi-structured data to JiZhi Analytics, the platform intelligently selects matching analytical algorithms to identify the optimal AI model.

Moreover, the Jizhi Analytics Platform can complete all technical analyses—including data preprocessing, baseline analysis, and advanced analysis—with a single click. This means that users can obtain the required analytical results without spending considerable time learning skills such as data analysis and modeling.。

For example, in the areas of intelligent data governance and automated baseline analysis, JiZhi Analytics has reduced the time required for relevant variable screening by 75%, while in intelligent parameter optimization modeling, it can shorten the modeling time for clinical prediction models by 90%.

The efficiency and intelligence behind JiZhi Analytics are attributable to its team background and algorithmic capabilities.

Xu Yuan, the founder of JiZhi Analytics, graduated with a degree in Biomedical Engineering from the School of Medicine at Sun Yat-sen University. He has long been engaged in research related to medical big data and has led or participated in more than ten national and provincial-level projects. It was precisely his academic background and professional experience that made Xu Yuan realize that,The need for medical data analysis is prevalent among clinicians and medical students.

Dr. Yang Tong, Co-Founder and CTO, graduated from Boston University and served as a researcher in the Computer Science Department at Brandeis University; he is an expert in machine learning and deep learning. Dr. Jiang Long, Academic Advisor, earned his medical degree from the University of Maryland and has published more than 10 SCI-indexed papers.

The team’s interdisciplinary background in medical big data, artificial intelligence, and other healthcare-related fields not only fosters empathy with researchers but also enables the team to identify and address the pain points and needs of clinical research more quickly and precisely.

It is precisely because the core team possesses a professional background that JiZhi Analytics has been able to integrate and optimize over one hundred algorithms and models, while also achieving intelligent matching of these algorithms and models. This constitutes the second advantage of JiZhi Analytics, as described by Xu Yuan. “The integration and standardization of diverse algorithms themselves present a significant challenge.”

When discussing the differences between Jizhi Analytics and other medical data analysis platforms,Xu Yuan stated that currently, mainstream data analysis software suffers from three major drawbacks: first, slow version updates result in a lack of newer algorithms; second, there is a certain barrier to entry for users; and third, the software fails to provide timely feedback or engage in real-time interaction with users. In contrast, the Jizhi Analysis Cloud Platform offers user-friendly operations, maintains real-time communication with users, and updates its analytical methods on a monthly basis.

In terms of promotion, VCBeat has learned that since its official launch in July 2021, Jizhi Analysis has provided clinical research-related services to more than 4,000 clinical researchers through word-of-mouth referrals. Currently, there are nearly 3,000 ongoing clinical research projects, and the company has established collaborations with more than ten pharmaceutical companies and medical institutions.

According to the development roadmap of JiZhi Analytics, it is currently in its early stages: attracting users through free analytical features and deeply exploring user needs to optimize platform functionalities.

In the future,The development goals of JiZhi Analytics are primarily threefold: further enriching and refining platform functionalities; aligning with the domestic trend of establishing research-oriented hospitals to realize an integrated system combining industry, academia, and research with community engagement; and building an AI-driven platform for the translation of precision medicine products.

As previously mentioned, JiZhi Analysis is currently primarily focused on its B2C business, with its built-in algorithms and models consisting mainly of general-purpose ones that may be used in clinical research. However, this clearly falls short of meeting the diverse needs of clinical scientific research.

Therefore,VBInsight will also provide customized services in the future, including study design, clinical project management, and manuscript generation.

In terms of platform ecosystem, Jizhi Analysis will further build an open-source, closed-loop shared community based on the “user-community-content-product” model. It will attract PGC and UGC contributors to upload models to a shared model pool through various incentive mechanisms, select high-quality models to form a product model library, and thereby facilitate the commercialization of models from the pool.

Additionally,Regarding its product lineup, Xu Yuan revealed to VCBeat that Jizhi Analysis will focus heavily on AI-driven diagnostic and therapeutic products in the future.“In the future, once we have accumulated a substantial user base, we aim to collaborate with external partners through joint research projects to co-develop products with shared intellectual property rights.”

At the end of the interview,Xu Yuan expressed a strong willingness to collaborate with hospitals. “Currently, many hospitals in China are establishing big data analytics centers, but they lack professional analysts to conduct data analysis. I believe the future trend may involve hospitals engaging third-party enterprises to provide data analytics services, and Jizhi Analytics is eager to embrace this opportunity.”

In the long run, with the rise of the medical big data industry, the state’s increasing emphasis on clinical research, and the accelerated localization of products in related fields, the era of new healthcare infrastructure has already begun. Jizhi Analysis hopes to become a participant in this development.