ArticleCancers2022
How AI Can Help in the Diagnostic Dilemma of Pulmonary Nodules.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- An Expert Committee-Driven Adaptive Framework for Multicenter Pulmonary Nodule Classification Using AI-Derived Quantitative CT Features.Journal of imaging informatics in medicine · 2026Article
- The segmentation of nanoparticles with a novel approach of HRUScientific reports · 2025Article
- Artificial intelligence in automated detection of lung nodules: a narrative review.International journal of physiology, pathophysiology and pharmacology · 2025Review
- A concentrated machine learning-based classification system for age-related macular degeneration (AMD) diagnosis using fundus images.Scientific reports · 2024Article
- An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis.Scientific reports · 2024Article
- Review
- Review
- A Lower False Positive Pulmonary Nodule Detection Approach for Early Lung Cancer Screening.Diagnostics (Basel, Switzerland) · 2022Article
- Artificial Intelligence in Lung Cancer Imaging: Unfolding the Future.Diagnostics (Basel, Switzerland) · 2022Review
- Research on CT Lung Segmentation Method of Preschool Children based on Traditional Image Processing and ResUnet.Computational and mathematical methods in medicine · 2022Review
- Deep learning-based growth prediction for sub-solid pulmonary nodules on CT images.Frontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
Pulmonary nodules are the precursors of bronchogenic carcinoma, its early detection facilitates early treatment which save a lot of lives. Unfortunately, pulmonary nodule detection and classification are liable to subjective variations with high rate of missing small cancerous lesions which opens the way for implementation of artificial intelligence (AI) and computer aided diagnosis (CAD) systems. The field of deep learning and neural networks is expanding every day with new models designed to overcome diagnostic problems and provide more applicable and simply used models. We aim in this review to briefly discuss the current applications of AI in lung segmentation, pulmonary nodule detection and classification.
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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.