ArticleRisk management and healthcare policy2021
Artificial Intelligence System Application in Miliary Lung Metastasis: Experience from a Rare Case.
Article in Risk management and healthcare policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Case Report: Cracking the case: unique presentation of pulmonary sarcomatoid carcinoma with spherical lung metastases.Frontiers in medicine · 2025Article
- Precautionary Recommendation System in Risk Management: A FMEA-Based Approach.Risk management and healthcare policy · 2025Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionMiliary 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.
conclusionThis 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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.