Papers Cancer Classification
“Cancer Classification” 태그가 달린 논문 260편 · 필터 해제
Robust Classification of Oral Cancer with Limited Training Data
Oral cancer ranks among the most prevalent cancers globally, with a particularly high mortality rate in regions lacking adequate healthcare access. Early diagnosis is crucial for reducing mortality; however, challenges p…
Cancer ClassificationBayesian InferenceA Novel Hybrid Deep Learning and Chaotic Dynamics Approach for Thyroid Cancer Classification
Timely and accurate diagnosis is crucial in addressing the global rise in thyroid cancer, ensuring effective treatment strategies and improved patient outcomes. We present an intelligent classification method that couple…
Cancer ClassificationEfficient Breast and Ovarian Cancer Classification via ViT-Based Preprocessing and Transfer Learning
Cancer is one of the leading health challenges for women, specifically breast and ovarian cancer. Early detection can help improve the survival rate through timely intervention and treatment. Traditional methods of detec…
Multi-class ClassificationCancer ClassificationBinary ClassificationTransfer LearningAccurate Thyroid Cancer Classification using a Novel Binary Pattern Driven Local Discrete Cosine Transform Descriptor
In this study, we develop a new CAD system for accurate thyroid cancer classification with emphasis on feature extraction. Prior studies have shown that thyroid texture is important for segregating the thyroid ultrasound…
Cancer ClassificationBreast Cancer Detection in Thermographic Images via Diffusion-Based Augmentation and Nonlinear Feature Fusion
Data scarcity hinders deep learning for medical imaging. We propose a framework for breast cancer classification in thermograms that addresses this using a Diffusion Probabilistic Model (DPM) for data augmentation. Our D…
Breast Cancer DetectionCancer ClassificationData AugmentationInterpretable Deep Transfer Learning for Breast Ultrasound Cancer Detection: A Multi-Dataset Study
Breast cancer remains a leading cause of cancer-related mortality among women worldwide. Ultrasound imaging, widely used due to its safety and cost-effectiveness, plays a key role in early detection, especially in patien…
Breast Cancer DetectionCancer ClassificationTransfer LearningMulti-Scale Deep Learning for Colon Histopathology: A Hybrid Graph-Transformer Approach
Colon cancer also known as Colorectal cancer, is one of the most malignant types of cancer worldwide. Early-stage detection of colon cancer is highly crucial to prevent its deterioration. This research presents a hybrid …
Cancer ClassificationMorphGen: Morphology-Guided Representation Learning for Robust Single-Domain Generalization in Histopathological Cancer Classification
Domain generalization in computational histopathology is hindered by heterogeneity in whole slide images (WSIs), caused by variations in tissue preparation, staining, and imaging conditions across institutions. Unlike ma…
Representation LearningDomain GeneralizationCancer ClassificationNuclear SegmentationExplainable Knowledge Distillation for Efficient Medical Image Classification
This study comprehensively explores knowledge distillation frameworks for COVID-19 and lung cancer classification using chest X-ray (CXR) images. We employ high-capacity teacher models, including VGG19 and lightweight Vi…
Medical Image ClassificationComputational EfficiencyKnowledge DistillationCancer ClassificationA Novel cVAE-Augmented Deep Learning Framework for Pan-Cancer RNA-Seq Classification
Pan-cancer classification using transcriptomic (RNA-Seq) data can inform tumor subtyping and therapy selection, but is challenging due to extremely high dimensionality and limited sample sizes. In this study, we propose …
Cancer ClassificationProstate Cancer Classification Using Multimodal Feature Fusion and Explainable AI
Prostate cancer, the second most prevalent male malignancy, requires advanced diagnostic tools. We propose an explainable AI system combining BERT (for textual clinical notes) and Random Forest (for numerical lab data) t…
Computational EfficiencyCancer ClassificationFeature ImportanceHybrid Deep Learning and Handcrafted Feature Fusion for Mammographic Breast Cancer Classification
Automated breast cancer classification from mammography remains a significant challenge due to subtle distinctions between benign and malignant tissue. In this work, we present a hybrid framework combining deep convoluti…
Computational EfficiencyCancer ClassificationAdvanced cervical cancer classification: enhancing pap smear images with hybrid PMD Filter-CLAHE
Cervical cancer remains a significant health problem, especially in developing countries. Early detection is critical for effective treatment. Convolutional neural networks (CNN) have shown promise in automated cervical …
Cancer ClassificationUncertainty-Aware Deep Learning for Automated Skin Cancer Classification: A Comprehensive Evaluation
Accurate and reliable skin cancer diagnosis is critical for early treatment and improved patient outcomes. Deep learning (DL) models have shown promise in automating skin cancer classification, but their performance can …
Cancer ClassificationLesion ClassificationMedical DiagnosisSkin Cancer Classification+4Integrating Complexity and Biological Realism: High-Performance Spiking Neural Networks for Breast Cancer Detection
Spiking Neural Networks (SNNs) event-driven nature enables efficient encoding of spatial and temporal features, making them suitable for dynamic time-dependent data processing. Despite their biological relevance, SNNs ha…
Breast Cancer DetectionCancer ClassificationDeep LearningInvestigating Quantum Feature Maps in Quantum Support Vector Machines for Lung Cancer Classification
In recent years, quantum machine learning has emerged as a promising intersection between quantum physics and artificial intelligence, particularly in domains requiring advanced pattern recognition such as healthcare. Th…
Cancer ClassificationDiagnosticLung Cancer DiagnosisQuantum Machine Learning+1Optimizing Deep Learning for Skin Cancer Classification: A Computationally Efficient CNN with Minimal Accuracy Trade-Off
The rapid advancement of deep learning in medical image analysis has greatly enhanced the accuracy of skin cancer classification. However, current state-of-the-art models, especially those based on transfer learning like…
Cancer ClassificationMedical Image AnalysisSkin Cancer ClassificationTransfer LearningAn Artificial Intelligence Model for Early Stage Breast Cancer Detection from Biopsy Images
Accurate identification of breast cancer types plays a critical role in guiding treatment decisions and improving patient outcomes. This paper presents an artificial intelligence enabled tool designed to aid in the ident…
Breast Cancer DetectionCancer ClassificationValidation of Conformal Prediction in Cervical Atypia Classification
Deep learning based cervical cancer classification can potentially increase access to screening in low-resource regions. However, deep learning models are often overconfident and do not reliably reflect diagnostic uncert…
Cancer ClassificationClassificationConformal PredictionDeep Learning+2Breast Cancer Classification in Deep Ultraviolet Fluorescence Images Using a Patch-Level Vision Transformer Framework
Breast-conserving surgery (BCS) aims to completely remove malignant lesions while maximizing healthy tissue preservation. Intraoperative margin assessment is essential to achieve a balance between thorough cancer resecti…
Cancer ClassificationClassificationDiagnostic