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Artificial Intelligence System Application in Miliary Lung Metastasis: Experience from a Rare Case.
Zhang, Yu; Chen, Yan; Li, Kun; Jiang, Wen; Zhang, Bi-Cheng.
  • Zhang Y; Department of Pathology, General Hospital of Central Theater Command of the People's Liberation Army, Wuhan, 430070, People's Republic of China.
  • Chen Y; Department of Anesthesiology, General Hospital of Central Theater Command of the People's Liberation Army, Wuhan, 430070, People's Republic of China.
  • Li K; Department of Anesthesiology, General Hospital of Central Theater Command of the People's Liberation Army, Wuhan, 430070, People's Republic of China.
  • Jiang W; Department of Health Medicine, General Hospital of Central Theater Command of the People's Liberation Army, Wuhan, 430070, People's Republic of China.
  • Zhang BC; Cancer Center, Renmin Hospital of Wuhan University, Wuhan, 430060, People's Republic of China.
Risk Manag Healthc Policy ; 14: 2825-2829, 2021.
Article in English | MEDLINE | ID: covidwho-1317169
ABSTRACT

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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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report Language: English Journal: Risk Manag Healthc Policy Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report Language: English Journal: Risk Manag Healthc Policy Year: 2021 Document Type: Article