In recent years, China’s healthcare system reform has been continuously deepening, with third-party medical laboratories gradually transitioning from a “supplementary role” to an important component of the healthcare service system. With the introduction of regulations such as the “Basic Standards and Management Specifications for Medical Laboratories”, the requirements for industry access and operational standardization have been clarified, and increasing attention has been paid to compliance issues in the medical laboratory industry. This article systematically outlines the regulatory framework for domestic third-party medical laboratories, covering key aspects such as administrative approvals, quality management, cost control, and industry supervision. It aims to provide actionable guidance for practitioners, and promote the compliant operation and service quality improvement of third-party medical laboratories.
Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language model technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. This article reviews the research progress and applications of large language models in assisting with lung cancer diagnosis, tumor feature extraction, staging, analysis of disease progression and outcomes, treatment recommendations, clinical documentation generation, and patient medical education. We further analyze the current challenges and opportunities, and provide an outlook on the future development of specialized large language models for lung cancer.