ArticleBioMed research international2022
Lung Cancer Classification and Prediction Using Machine Learning and Image Processing.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 12 papers.
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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
12 citing papers in PubMed.
- Enriched lung cancer classification approach using an optimized hybrid deep learning approach.Scientific reports · 2025Article
- SVMVGGNet-16: A Novel Machine and Deep Learning Based Approaches for Lung Cancer Detection Using Combined SVM and VGGNet-16.Current medical imaging · 2025Article
- Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.Journal of imaging informatics in medicine · 2024Article
- An Advanced Lung Carcinoma Prediction and Risk Screening Model Using Transfer Learning.Diagnostics (Basel, Switzerland) · 2024Article
- EDTNet: A spatial aware attention-based transformer for the pulmonary nodule segmentation.PloS one · 2024Article
- Efficient lung cancer detection using computational intelligence and ensemble learning.PloS one · 2024Article
- Retracted: Lung Cancer Classification and Prediction Using Machine Learning and Image Processing.BioMed research international · 2024Article
- Machine Learning for Prediction of Non-Small Cell Lung Cancer Based on Inflammatory and Nutritional Indicators in Adults: A Cross-Sectional Study.Cancer management and research · 2024Article
- Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment.Scientific reports · 2023Article
- Ensemble Federated Learning Approach for Diagnostics of Multi-Order Lung Cancer.Diagnostics (Basel, Switzerland) · 2023Article
- Performance evaluation of deep learning techniques for lung cancer prediction.Soft computing · 2023Article
- A TDD Framework for Automated Monitoring in Internet of Things with Machine Learning.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
- Retraction · 2024-01-09Compromised Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Paper Mill · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lung cancer is a potentially lethal illness. Cancer detection continues to be a challenge for medical professionals. The true cause of cancer and its complete treatment have still not been discovered. Cancer that is caught early enough can be treated. Image processing methods such as noise reduction, feature extraction, identification of damaged regions, and maybe a comparison with data on the medical history of lung cancer are used to locate portions of the lung that have been impacted by cancer. This research shows an accurate classification and prediction of lung cancer using technology that is enabled by machine learning and image processing. To begin, photos need to be gathered. In the experimental investigation, 83 CT scans from 70 distinct patients were utilized as the dataset. The geometric mean filter is used during picture preprocessing. As a consequence, image quality is enhanced. The
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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.