Infervision Showcases Multimodal Clinical Solutions at RSNA, Enabling Cross-Imaging Device Integration
On November 25, 2018, local time, the Radiological Society of North America (RSNA) Annual Meeting, the largest and most representative premier medical conference showcasing the future direction of the global radiology industry, opened at the McCormick Place Convention Center in Chicago, USA, gathering top experts and scholars from around the world. VCBeat (WeChat ID: vcbeat) has learned that Infervision unveiled its multi-modal clinical scenario solutions, with its latest versions of InferRead CT Lung, InferRead CT Chest, and emergency care solutions receiving widespread acclaim.
Infervision believes that while artificial intelligence models play a crucial role in AI enterprises, possessing the technology alone does not guarantee the development of “good” AI products. While deeply cultivating its technological capabilities, Infervision also places significant emphasis on integrating technology with clinical scenarios, exploring more efficient and rational pathways for product validation. Due to the uneven levels of digital infrastructure and the varying speeds of hardware and software updates across hospital departments in China, there are substantial disparities in imaging equipment, scanning protocols, and information environments—both between different hospitals and even within individual institutions. These discrepancies initially posed significant challenges to the deployment of Infervision’s AI applications. Furthermore, achieving effective coordination and operational synergy among various internal departments presents a severe challenge to the development of innovative enterprises.
After four years of intensive development, Infervision’s AI models now achieve high recognition rates across nearly all imaging equipment vendors in the market, including international giants such as GPS (GE Healthcare, Philips, and Siemens Healthineers) as well as numerous Chinese manufacturers, covering their DICOM imaging data. The AI system has been successfully integrated with 48 RIS and PACS systems. To address configuration differences across departmental terminals, each AI product can be customized for specific applications. In clinical practice, improvements in AI performance have undoubtedly opened up new avenues for clinical research. By leveraging synergies among the Infervision Advanced Research Institute, the Clinical Research Collaboration Academy, and its solution offerings, the company has gradually established a closed-loop product validation pathway from model development to clinical application. This approach not only requires R&D teams to directly confront the practical applicability of AI products and gain early mastery of AI usage scenarios, but also provides a strong foundation for enhancing Infervision’s R&D capabilities, enabling continuous iteration and scaling of AI solutions across a broader market.
Currently, Infervision AI has broken through the technical barriers of single-disease detection and screening, effectively achieving horizontal and vertical expansion for individual diseases. Starting from disease prevention, it covers the entire process of disease screening, diagnosis, treatment, follow-up, and education, thereby creating a new pathway for AI-driven disease management. For instance, InferRead CT Lung now encompasses full-pathway functionalities, including nodule screening, differential diagnosis, qualitative analysis, and follow-up, while also supporting remote interaction and continuing education modules. This deepens capabilities within a single clinical scenario and overall enhances physicians’ diagnostic and treatment proficiency. The Infervision Clinical Research Institute and the Advanced Research Institute are jointly accelerating the in-depth implementation of AI solutions. To date, they have assisted in the diagnosis of 3.05 million patients, with 22,000 examinations supported daily.
Infervision’s multimodal clinical solutions showcased at RSNA support pulmonary nodule screening, quantitative functional analysis of COPD, quantitative calcium scoring, and bone disease management, aiming to build a one-stop service platform. Furthermore, multiple Infervision products are not limited to single-disease examinations; they maximize the respective advantages of X-ray and CT, unlock equipment value, and ultimately achieve cross-modality integration across imaging devices.
Infervision’s booth also attracted a large number of international experts and scholars, who affirmed Infervision’s scientific research and product achievements. Chen Kuan, founder of Infervision, stated, “Promoting the long-term development of artificial intelligence is a protracted campaign. It not only requires enterprises to continuously strengthen their technological R&D capabilities and innovative expansion capabilities, but also necessitates deeper integration with the medical field to build an AI industrial ecosystem encompassing infrastructure, technology, products, and applications, ultimately achieving AI empowerment across the entire medical imaging industry!”
The coming years will witness rapid development in the construction of smart healthcare in China. As a leading innovative technology enterprise, Infervision bears an unshirkable responsibility to continue strengthening its efforts in scientific research and clinical collaboration, conducting in-depth practical studies, stimulating the innovative vitality of physicians, and jointly advancing the development of AI as a medical discipline. Leveraging data accumulated within the healthcare industry and integrating artificial intelligence technologies, we aim to build disease prediction and management models and reshape healthcare service delivery. Addressing urgent public needs in education, healthcare, and elderly care, Infervision will accelerate the innovative application of artificial intelligence to provide the public with a personalized, diversified, and advanced AI service platform, thereby improving population health outcomes and accelerating the realization of smart healthcare in China.