ReviewIndian journal of surgical oncology2025
A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer.
Review in Indian journal of surgical oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The association between VEGF genetic variations and the risk of bronchopulmonary dysplasia in premature infants: a meta-analysis and systematic review.Frontiers in pediatrics · 2024Pooled it
- Artificial intelligence-assisted early screening of lung cancer and accurate diagnosis of pulmonary nodules: research progress and clinical prospects from radiomics to multi-omics integration: a narrative review.Journal of thoracic disease · 2026Review
- Theoretical applications of artificial intelligence in smart infusion pump technology: Expert panel insights.American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2026Article
- Artificial Intelligence in Lung Cancer: A Narrative Review of Recent Advances in Diagnosis, Biomarker Discovery, and Drug Development.Pharmaceutics · 2026Review
- Radiology artificial intelligence for prioritized imaging and diagnosis of lung cancer: qualitative interview analysis of stakeholder perspectives in Northern Ireland.Frontiers in medicine · 2026Article
- Decoding the Genetic Landscape of Postoperative Nausea and Vomiting in Cancer Surgery: A New Frontier in Personalized Medicine Driven by Genome-Wide Association Studies.Indian journal of surgical oncology · 2025Review
- GPU-Accelerated Artificial Intelligence Applications in Cancer Diagnosis, Imaging, and Treatment Planning.Asian Pacific journal of cancer prevention : APJCP · 2025Review
- Large-Scale Meta-Analysis of TNF-α rs1800629 Polymorphism in Schizophrenia: Evidence from 7,624 Cases and 8,933 Controls.Medeniyet medical journal · 2025Article
- Advancements in machine learning and biomarker integration for prenatal Down syndrome screening.Turkish journal of obstetrics and gynecology · 2025Article
- Machine learning applications in placenta accreta spectrum disorders.European journal of obstetrics & gynecology and reproductive biology: X · 2025Review
- ChatGPT-o1 Preview Outperforms ChatGPT-4 as a Diagnostic Support Tool for Ankle Pain Triage in Emergency Settings.Archives of academic emergency medicine · 2025Article
- Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects.Frontiers in pediatrics · 2025Review
- Prevalence of Interstitial Lung Disease in Patients with Primary Sjogren's Syndrome: A Systematic Review and Meta-analysis of Observational Studies : Prevalence of Interstitial Lung Disease in Patients with Primary Sjogren's Syndrome.Galen medical journal · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of artificial intelligence (AI) in lung cancer, particularly in surgical approaches, has significantly transformed the healthcare landscape. AI has demonstrated remarkable advancements in early lung cancer detection, precise medical image analysis, and personalized treatment planning, all of which are crucial for surgical interventions. By analyzing extensive datasets, AI algorithms can identify patterns and anomalies in lung scans, facilitating timely diagnoses and enhancing surgical outcomes. Furthermore, AI can detect subtle indicators that may be overlooked by human practitioners, leading to quicker intervention and more effective treatment strategies. The technology can also predict patient responses to surgical treatments, enabling tailored care plans that improve recovery rates. In addition to surgical applications, AI streamlines administrative tasks such as record management and appointment scheduling, allowing healthcare providers to concentrate on delivering high-quality care. The integration of AI with genomics and precision medicine holds the potential to further refine surgical approaches in lung cancer treatment by developing targeted strategies that enhance effectiveness and minimize side effects. Despite challenges related to data privacy and regulatory concerns, the ongoing advancements in AI, coupled with collaboration between healthcare professionals and AI experts, suggest a promising future for lung cancer care. This article explores how AI addresses the challenges of lung cancer treatment, focusing on current advancements, obstacles, and the future potential of surgical applications.
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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.