ReviewCancer cell international2021
The current issues and future perspective of artificial intelligence for developing new treatment strategy in non-small cell lung cancer: harmonization of molecular cancer biology and artificial intelligence.
Review in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
30 citing papers in PubMed.
- Multi-omics and artificial intelligence for precision drug discovery and potential clinical applications.Signal transduction and targeted therapy · 2026Review
- Artificial Intelligence in Lung Cancer: A Narrative Review of Recent Advances in Diagnosis, Biomarker Discovery, and Drug Development.Pharmaceutics · 2026Review
- Multi-omics integration in deciphering non-small cell lung cancer drug resistance: current status, challenges, and future prospects.Hereditas · 2026Review
- Evolving non-invasive biomarkers in NSCLC immunotherapy: integrating liquid biopsy and multi-omics profiling for precision oncology.Frontiers in immunology · 2026Review
- AI-engineered multifunctional nanoplatforms: synergistically bridging precision diagnosis and intelligent therapy in next-generation oncology.Journal of nanobiotechnology · 2025Review
- Artificial Intelligence and Machine Learning in Lung Cancer: Advances in Imaging, Detection, and Prognosis.Cancers · 2025Review
- Spatial omics technology potentially promotes the progress of tumor immunotherapy.British journal of cancer · 2025Review
- Deep learning-driven multi-omics analysis: enhancing cancer diagnostics and therapeutics.Briefings in bioinformatics · 2025Review
- Recent advances and challenges in colorectal cancer: From molecular research to treatment.World journal of gastroenterology · 2025Review
- From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies.Molecular biotechnology · 2025Review
- Emerging molecular testing paradigms in non-small cell lung cancer management-current perspectives and recommendations.The oncologist · 2025Review
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Innovative laboratory techniques shaping cancer diagnosis and treatment in developing countries.Discover oncology · 2025Review
- Artificial intelligence in cancer pathology: Applications, challenges, and future directions.CytoJournal · 2025Review
- Neuroprotective Potential of Free Radical-Scavenging Nanoparticles in Addressing Inflammation and Obesity.IET nanobiotechnology · 2025Review
- Approaches to modeling cancer metastasis: from bench to bedside.Frontiers in oncology · 2025Review
- Article
- Artificial intelligence in lung cancer.Annals of translational medicine · 2024Article
- Artificial intelligence in lung cancer screening: Detection, classification, prediction, and prognosis.Cancer medicine · 2024Review
- Multiomic Investigations into Lung Health and Disease.Microorganisms · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Comprehensive analysis of omics data, such as genome, transcriptome, proteome, metabolome, and interactome, is a crucial technique for elucidating the complex mechanism of cancer onset and progression. Recently, a variety of new findings have been reported based on multi-omics analysis in combination with various clinical information. However, integrated analysis of multi-omics data is extremely labor intensive, making the development of new analysis technology indispensable. Artificial intelligence (AI), which has been under development in recent years, is quickly becoming an effective approach to reduce the labor involved in analyzing large amounts of complex data and to obtain valuable information that is often overlooked in manual analysis and experiments. The use of AI, such as machine learning approaches and deep learning systems, allows for the efficient analysis of massive omics data combined with accurate clinical information and can lead to comprehensive predictive models that will be desirable for further developing individual treatment strategies of immunotherapy and molecular target therapy. Here, we aim to review the potential of AI in the integrated analysis of omics data and clinical information with a special focus on recent advances in the discovery of new biomarkers and the future direction of personalized medicine in non-small 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.