Concept and prospect of the Human-Computer Multi-Disciplinary team (MDT) in pulmonary nodule evaluation

Abstract

Lung cancer is the leading cause of cancer-related deaths worldwide. Early diagnosis and treatment play a crucial role in improving the prognosis for lung cancer. However, the issue of overtreatment and delayed diagnosis remains prevalent due to the considerable limitations of manual film review in facilitating early detection and treatment of lung cancer. In recent years, artificial intelligence (AI) has emerged as a valuable tool for clinicians to screen and evaluate benign and malignant pulmonary nodules, offering numerous advantages. Nevertheless, the sensitivity and specificity of AI are neither sufficient to completely replace medical experts nor capable of assuming direct responsibility for clinical diagnosis and treatment.

Therefore, we propose the concept of a Human-Computer Multi-Disciplinary Team (MDT), which involves collaborative decision-making between human physicians and AI systems. The human-computer MDT approach in pulmonary nodule evaluation presents a novel model for diagnosis and treatment, leveraging the respective strengths of human expertise and AI capabilities. This review provides an overview of the background, medical application, advantages and limitations, future trends, and reporting format of the Human-Computer MDT in pulmonary nodule evaluation.

Its aim is to explore standardized methods for enhancing early diagnosis in lung cancer. With the rapid advancement of AI and the field of meta-cosmic medicine, human-computer MDT are expected to become more widespread and play an important role in the implementation of the Healthy China 2030 plan, particularly in improving primary medical care in the future.