With the development of artificial intelligence, what kind of surprise will it bring to medical treatment?

With the rapid advancement of medical artificial intelligence, its applications are becoming increasingly diverse. Today, AI is involved in various areas of medicine, such as abdominal tumor analysis systems, precise liver cancer radiofrequency ablation surgery, ultrasound robots, and intelligent diagnostic tools for childhood growth delays. In addition to these technological innovations, AI is also playing a crucial role in providing doctors with intelligent medical tools and clinical decision support systems. Let’s explore more about how AI is transforming the healthcare landscape. Data remains one of the biggest challenges in the development of artificial intelligence. At the 2018 China Hospital Information Network Conference, Yang Jijiang from Tsinghua University emphasized that “data is the foundation of AI.” Due to the complexity of medical environments and decision-making processes, many AI-driven medical companies are shifting their focus from algorithm development to data collection and management, recognizing that high-quality data is essential for accurate AI performance. The application of AI in medicine spans multiple domains. Professor Kong Dexing from Zhejiang University highlighted several key areas, including AI-assisted therapy, AI-based medical imaging, precision surgery, drug discovery, and health management solutions like virtual nurses. In Western countries, AI is already being used for self-monitoring, early dementia detection, pancreatic cancer diagnosis, and ophthalmic imaging. IBM Watson is a well-known example of AI in healthcare. As an AI cloud platform, it helps oncologists make treatment decisions. Since 2017, Baiyang Intelligent Technology has been the exclusive distributor of Watson for oncology in China, with Watson Cancer Consultation Centers now established in 29 top-tier hospitals across the country. In practical applications, AI has made significant progress. For instance, China has developed an abdominal medical image processing system that has saved lives by accurately identifying treatable conditions. A case study showed that a patient initially thought to have an untreatable pancreatic tumor was found to be eligible for surgery after AI-assisted analysis, leading to a successful operation and recovery. Ultrasonic robots are another promising area of AI in healthcare. With the help of deep learning algorithms, these robots can perform automatic screening, intelligent diagnosis, and even assist in surgical planning. A database of over 24,000 samples has been created, and AI-powered ultrasonic robots have demonstrated impressive accuracy in detecting thyroid nodules and determining their benign or malignant nature. Despite the progress, ensuring the accuracy of medical data remains a critical challenge. AI models trained on small or poorly curated datasets may not perform well when applied to broader populations. Yang Jijiang noted that while big data has fueled AI breakthroughs, effective utilization is key. Cleaning and organizing large volumes of medical data is a labor-intensive process but essential for reliable AI outcomes. AI is still primarily an auxiliary tool in healthcare, supporting doctors rather than replacing them. Systems like Ali Health’s “Doctor You” aim to enhance overall medical AI capabilities, while other platforms integrate AI and big data to provide clinical decision support. Ultimately, AI’s greatest contribution lies in improving data analysis efficiency and offering valuable insights to doctors. While perfection is still a long way off, continuous improvements through real-world applications will help AI become an even more powerful tool in the future.

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