ReviewBiomedical engineering online2018
Advances in intelligent diagnosis methods for pulmonary ground-glass opacity nodules.
Review in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Risk factors for the growth of ground-glass nodules in the lungs: A systematic review and meta-analysis.Clinics (Sao Paulo, Brazil) · 2025Pooled it
- Computer-aided diagnosis of primary membranous nephropathy using expert system.Biomedical engineering online · 2023Article
- CT imaging indications correlate with the degree of lung adenocarcinoma infiltration.Frontiers in oncology · 2023Article
- Evaluation of the dual vascular supply patterns in ground-glass nodules with a dynamic volume computed tomography.World journal of radiology · 2022Article
- Pulmonary Nodule Clinical Trial Data Collection and Intelligent Differential Diagnosis for Medical Internet of Things.Contrast media & molecular imaging · 2022Article
- An Intervention to Tag Findings Suspicious for Lung Cancer on Chest Computed Tomography Has Good Sensitivity and Number Needed to Diagnose.The Permanente journal · 2021Article
- Establishment and verification of a prediction model based on clinical characteristics and positron emission tomography/computed tomography (PET/CT) parameters for distinguishing malignant from benign ground-glass nodules.Quantitative imaging in medicine and surgery · 2021Article
- Invasive Prediction of Ground Glass Nodule Based on Clinical Characteristics and Radiomics Feature.Frontiers in genetics · 2021Article
- Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning.Frontiers in oncology · 2021Article
- Comprehensive Perspective for Lung Cancer Characterisation Based on AI Solutions Using CT Images.Journal of clinical medicine · 2020Article
- Predicting the invasiveness of lung adenocarcinomas appearing as ground-glass nodule on CT scan using multi-task learning and deep radiomics.Translational lung cancer research · 2020Article
- CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction.BMC cancer · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Pulmonary nodule is one of the important lesions of lung cancer, mainly divided into two categories of solid nodules and ground glass nodules. The improvement of diagnosis of lung cancer has significant clinical significance, which could be realized by machine learning techniques. At present, there have been a lot of researches focusing on solid nodules. But the research on ground glass nodules started late, and lacked research results. This paper summarizes the research progress of the method of intelligent diagnosis for pulmonary nodules since 2014. It is described in details from four aspects: nodular signs, data analysis methods, prediction models and system evaluation. This paper aims to provide the research material for researchers of the clinical diagnosis and intelligent analysis of lung cancer, and further improve the precision of pulmonary ground glass nodule diagnosis.
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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.