ArticleDiagnostics (Basel, Switzerland)2023
An Explainable Classification Method Based on Complex Scaling in Histopathology Images for Lung and Colon Cancer.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- A Hybrid Lung and Colon Histopathological Image Classification Framework Using MobileNetV3-Small Deep Features and Differential Evolution Optimization.Diagnostics (Basel, Switzerland) · 2026Article
- Dual-Path Convolutional Neural Network with Squeeze-and-Excitation Attention for Lung and Colon Histopathology Classification.Journal of imaging · 2025Article
- Enhanced Diagnosis of Lung and Colon Cancer Severity Through Deep Feature Analysis Using DenseNet201 and SVM With Histopathological Images: A Super-Resolution Approach.Cancer reports (Hoboken, N.J.) · 2025Article
- A Lightweight Cross-Gated Dual-Branch Attention Network for Colon and Lung Cancer Diagnosis from Histopathological Images.Medical sciences (Basel, Switzerland) · 2025Article
- Analyzing histopathological images using fused CNN features based on the geometric active contour method for early diagnosis of lung and colon cancer.Discover oncology · 2025Article
- An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging.Scientific reports · 2025Article
- Prognostic and therapeutic potential of copper-induced cell death-related lncRNAs in lung squamous cell carcinoma.Clinical and experimental medicine · 2025Article
- Advancements in Digital Cytopathology Since COVID-19: Insights from a Narrative Review of Review Articles.Healthcare (Basel, Switzerland) · 2025Review
- Advanced deep learning for multi-class colorectal cancer histopathology: integrating transfer learning and ensemble methods.Quantitative imaging in medicine and surgery · 2025Article
- Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model.Scientific reports · 2024Article
- Article
- Secure and Transparent Lung and Colon Cancer Classification Using Blockchain and Microsoft Azure.Advances in respiratory medicine · 2024Article
- Identification of Anomalies in Lung and Colon Cancer Using Computer Vision-Based Swin Transformer with Ensemble Model on Histopathological Images.Bioengineering (Basel, Switzerland) · 2024Article
- Automated Lung and Colon Cancer Classification Using Histopathological Images.Biomedical engineering and computational biology · 2024Article
- Computer-aided colorectal cancer diagnosis: AI-driven image segmentation and classification.PeerJ. Computer science · 2024Article
- Weighing the benefits of lymphadenectomy in early-stage colorectal cancer.Annals of surgical treatment and research · 2023Review
- An Efficient Combination of Convolutional Neural Network and LightGBM Algorithm for Lung Cancer Histopathology Classification.Diagnostics (Basel, Switzerland) · 2023Article
- Article
- ELW-CNN: An extremely lightweight convolutional neural network for enhancing interoperability in colon and lung cancer identification using explainable AI.Healthcare technology lettersArticle
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Authors and funding
5 authors.
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Abstract
Lung and colon cancers are among the leading causes of human mortality and morbidity. Early diagnostic work up of these diseases include radiography, ultrasound, magnetic resonance imaging, and computed tomography. Certain blood tumor markers for carcinoma lung and colon also aid in the diagnosis. Despite the lab and diagnostic imaging, histopathology remains the gold standard, which provides cell-level images of tissue under examination. To read these images, a histopathologist spends a large amount of time. Furthermore, using conventional diagnostic methods involve high-end equipment as well. This leads to limited number of patients getting final diagnosis and early treatment. In addition, there are chances of inter-observer errors. In recent years, deep learning has shown promising results in the medical field. This has helped in early diagnosis and treatment according to severity of disease. With the help of
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