Author: Zhang, Yu; Chen, Yan; Li, Kun; Jiang, Wen; Zhang, Bi-Cheng
                    Title: Artificial Intelligence System Application in Miliary Lung Metastasis: Experience from a Rare Case  Cord-id: s9og8ils  Document date: 2021_7_5
                    ID: s9og8ils
                    
                    Snippet: INTRODUCTION: Miliary intrapulmonary carcinomatosis (MIPC) is very rare in the existing literature. We reported a lung adenocarcinoma patient presented with over 200 uniform size pulmonary nodules in all lung lobes at the initial examination. The application of artificial intelligence (AI) in lung cancer has been gradually reported, but not yet reported in MIPC. The application of AI in this rare disease is worth exploring. PATIENT INFORMATION: A 57-year-old woman received chest computed tomogra
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: INTRODUCTION: Miliary intrapulmonary carcinomatosis (MIPC) is very rare in the existing literature. We reported a lung adenocarcinoma patient presented with over 200 uniform size pulmonary nodules in all lung lobes at the initial examination. The application of artificial intelligence (AI) in lung cancer has been gradually reported, but not yet reported in MIPC. The application of AI in this rare disease is worth exploring. PATIENT INFORMATION: A 57-year-old woman received chest computed tomography (CT) scan because of dry cough, intermittent chest wall and back pain for 3 weeks. CT imaging found over 200 uniform size pulmonary nodules in an evenly dispersed pattern at bilateral lungs with a 38×45mm new creature at the dorsal segment of the lower lobe of the left lung. However, as a very reliable diagnostic assistant system in CT imaging of lung cancer, AI can only identify 18 nodules in such classic metastatic lung cancer case. CONCLUSION: This case provides classical imaging figures as textbook-like, even though there is no such classic imaging of lung metastases in the existing textbooks. This medical imaging material will impress medical students and help them learn about the disease deeply. This medical imaging material can warn patients to recognize the horror of lung cancer metastasis and has good popularization of science. This medical imaging material presents a new challenge for AI.
 
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