Core Viewpoint - The highest level of medical intelligence should be L4, which emphasizes human-machine collaboration rather than a fully automated system, as expressed by Zhou Guoyi, Chief Scientist of KAILI Medical [1]. Group 1: AI in Healthcare - AI is rapidly transforming the healthcare industry, with advancements in disease screening, clinical diagnosis, risk assessment, and treatment decision-making [1]. - The global medical AI market is projected to exceed $100 billion by 2030, with medical imaging AI being one of the fastest-growing segments [1]. - KAILI Medical has been a pioneer in the systematic layout of ultrasound AI since 2016, adopting a "device + AI" strategy that integrates AI deeply into medical devices [2]. Group 2: Advantages of KAILI Medical's Approach - The "device + AI" strategy offers three core advantages: landing advantage, integration advantage, and performance advantage, allowing for optimal results with limited investment [2]. - KAILI Medical's approach ensures that AI assists doctors in intelligent device operation, completing comprehensive tasks rather than focusing on isolated steps [2][5]. - The company emphasizes the importance of high-quality data for the successful application of AI in clinical settings, which requires collaboration between medical professionals and engineers [8][9]. Group 3: Challenges and Solutions - Early challenges included the immaturity of deep learning frameworks and issues with reliability and scalability, which KAILI Medical overcame by developing its own framework and gradually enhancing hardware capabilities [4]. - The company faced concerns about the direction of its AI projects, but recognized the potential to transform traditional human-machine interaction in medical procedures [5]. - A significant challenge in developing specialized AI models is obtaining high-quality, well-distributed data, which is essential for effective algorithm performance [8]. Group 4: Future Directions - The future evolution of ultrasound AI will involve integrating multi-modal characteristics of ultrasound with AI multi-modal fusion technology to enhance diagnostic accuracy [10]. - KAILI Medical envisions a future where instruments, AI, and humans work seamlessly together, providing real-time diagnostic assistance to doctors [11]. - The relationship between AI and doctors is seen as a long-term collaboration, where AI serves as an assistant rather than a replacement, maintaining the human element in medical decision-making [10].

Core Viewpoint - The highest level of medical intelligence is considered to be L4, which emphasizes "human-machine collaboration" rather than a fully automated medical environment [1][20]. Industry Insights - The global medical AI market is projected to exceed $100 billion by 2030, with medical imaging AI being one of the fastest-growing segments [2]. - The company has been a pioneer in systematically laying out ultrasound AI since 2016, adopting a "device + AI" strategy that integrates AI deeply into medical devices [3][4]. Technological Development - The company focuses on three core advantages of its "device + AI" approach: implementation advantage, integration advantage, and performance advantage [4]. - The "Fengyan S-Fetus" technology, which integrates ultrasound technology with AI, has achieved significant milestones, including obtaining the first domestic prenatal ultrasound AI medical device certification [4][11]. Data and Model Training - High-quality, well-distributed data is crucial for the effective application of AI in clinical settings [5][15][16]. - The company collaborates with various medical institutions to build a clinical data cooperation system, ensuring compliance with ethical standards and data privacy [16]. Future Directions - The company aims to achieve a "fully intelligent machine" concept, where AI drives the entire clinical process, covering major application areas such as gynecology, obstetrics, cardiology, and more [21]. - The integration of visual models with large language models is being explored to enhance diagnostic capabilities [17]. Regulatory and Policy Considerations - The registration process for AI products is more stringent than for traditional medical devices, emphasizing the need for rigorous clinical trials and data integrity [12][11]. - There is a call for improved regulatory frameworks to support the integration of AI in healthcare, ensuring that AI can be effectively utilized while maintaining human oversight [22][23].