ReviewPrecision clinical medicine2020
The application of artificial intelligence and radiomics in lung cancer.
Review in Precision clinical medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.
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
29 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Artificial intelligence for lung cancer: a systematic review of head‑to‑head CT, FDG PET/CT, and multimodal models across screening, staging, and prognosis.BMC medical imaging · 2026Pooled it
- Diagnostic accuracy of CT and PET/CT radiomics in predicting lymph node metastasis in non-small cell lung cancer.European radiology · 2025Pooled it
- AI-Driven Multi-Omics Approaches for Deciphering Small-Cell Lung Cancer Heterogeneity Using Nucleic-Acid-Based Features.Cancers · 2026Review
- Artificial intelligence (AI)-driven ensemble model for comprehensive chest X-ray abnormality detection and deployment.The Indian journal of medical research · 2026Article
- Article
- [Advances in radiomics for early diagnosis and precision treatment of lung cancer].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- Non-invasive identification of TKI-resistant NSCLC: a multi-model AI approach for predicting EGFR/TP53 co-mutations.BMC pulmonary medicine · 2025Article
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.Frontiers in medicine · 2025Article
- Applications and challenges of multi-omics approaches in lung cancer research and precision treatment.Frontiers in genetics · 2025Review
- Advances in the mechanisms, imaging characteristics and management strategies for immune checkpoint inhibitor-related pneumonitis.Frontiers in immunology · 2025Review
- Non-invasive, fast, and high-performance EGFR gene mutation prediction method based on deep transfer learning and model stacking for patients with Non-Small Cell Lung Cancer.European journal of radiology open · 2024Article
- Data-driven risk stratification and precision management of pulmonary nodules detected on chest computed tomography.Nature medicine · 2024Article
- Deep learning for precise diagnosis and subtype triage of drug-resistant tuberculosis on chest computed tomography.MedComm · 2024Article
- Novel tools for early diagnosis and precision treatment based on artificial intelligence.Chinese medical journal pulmonary and critical care medicine · 2023Review
- Clinical applications of radiomics in non-small cell lung cancer patients with immune checkpoint inhibitor-related pneumonitis.Frontiers in immunology · 2023Review
- Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.PLOS digital health · 2023Article
- Development and validation of an abnormality-derived deep-learning diagnostic system for major respiratory diseases.NPJ digital medicine · 2022Article
- The Crohn's-like lymphoid reaction density: a new artificial intelligence quantified prognostic immune index in colon cancer.Cancer immunology, immunotherapy : CII · 2022Article
- Predicting EGFR and PD-L1 Status in NSCLC Patients Using Multitask AI System Based on CT Images.Frontiers in immunology · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is one of the most leading causes of death throughout the world, and there is an urgent requirement for the precision medical management of it. Artificial intelligence (AI) consisting of numerous advanced techniques has been widely applied in the field of medical care. Meanwhile, radiomics based on traditional machine learning also does a great job in mining information through medical images. With the integration of AI and radiomics, great progress has been made in the early diagnosis, specific characterization, and prognosis of lung cancer, which has aroused attention all over the world. In this study, we give a brief review of the current application of AI and radiomics for precision medical management in lung cancer.
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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.