Papers Cancer Classification
“Cancer Classification” 태그가 달린 논문 260편 · 필터 해제
Joint-Individual Fusion Structure with Fusion Attention Module for Multi-Modal Skin Cancer Classification
Most convolutional neural network (CNN) based methods for skin cancer classification obtain their results using only dermatological images. Although good classification results have been shown, more accurate results can …
Cancer ClassificationClassificationDecision MakingMulti-modal Classification+1Double Integral Enhanced Zeroing Neural Network Optimized with ALSOA fostered Lung Cancer Classification using CT Images
Lung cancer is one of the deadliest diseases and the leading cause of illness and death. Since lung cancer cannot predicted at premature stage, it able to only be discovered more broadly once it has spread to other lung …
Cancer ClassificationGene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information
Benefiting from the advancements in deep learning, various genomic analytical techniques, such as survival analysis, classification of tumors and their subtypes, and exploration of specific pathways, have significantly e…
Cancer ClassificationClassificationPrognosisSurvival AnalysisMedISure: Towards Assuring Machine Learning-based Medical Image Classifiers using Mixup Boundary Analysis
Machine learning (ML) models are becoming integral in healthcare technologies, presenting a critical need for formal assurance to validate their safety, fairness, robustness, and trustworthiness. These models are inheren…
Cancer ClassificationFairnessTumour ClassificationBreast Cancer classification by adaptive weighted average ensemble of previously trained models
Breast cancer is a serious disease that inflicts millions of people each year, and the number of cases is increasing. Early detection is the best way to reduce the impact of the disease. Researchers have developed many t…
Cancer ClassificationHarnessing Transformers: A Leap Forward in Lung Cancer Image Detection
This paper discusses the role of Transfer Learning (TL) and transformers in cancer detection based on image analysis. With the enormous evolution of cancer patients, the identification of cancer cells in a patient's body…
Cancer ClassificationComputed Tomography (CT)Transfer LearningLeveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data
Breast cancer screening, primarily conducted through mammography, is often supplemented with ultrasound for women with dense breast tissue. However, existing deep learning models analyze each modality independently, miss…
Cancer ClassificationClass-Specific Data Augmentation: Bridging the Imbalance in Multiclass Breast Cancer Classification
Breast Cancer is the most common cancer among women, which is also visible in men, and accounts for more than 1 in 10 new cancer diagnoses each year. It is also the second most common cause of women who die from cancer. …
Cancer ClassificationData AugmentationTransfer LearningVisual Attention Prompted Prediction and Learning
Visual explanation (attention)-guided learning uses not only labels but also explanations to guide model reasoning process. While visual attention-guided learning has shown promising results, it requires a large number o…
Cancer ClassificationDecision MakingPredictionAttention-Map Augmentation for Hypercomplex Breast Cancer Classification
Breast cancer is the most widespread neoplasm among women and early detection of this disease is critical. Deep learning techniques have become of great interest to improve diagnostic performance. However, distinguishing…
Breast Cancer Histology Image ClassificationBreast Tumour ClassificationCancer ClassificationClassification+2Virchow: A Million-Slide Digital Pathology Foundation Model
The use of artificial intelligence to enable precision medicine and decision support systems through the analysis of pathology images has the potential to revolutionize the diagnosis and treatment of cancer. Such applica…
Breast Tumour ClassificationCancer ClassificationmodelSelf-Supervised Learning+1Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis
In recent years, many mammographic image analysis methods have been introduced for improving cancer classification tasks. Two major issues of mammogram classification tasks are leveraging multi-view mammographic informat…
Cancer ClassificationUser lung cancer classification using efficientnet from ct scan images
Lung cancer (LC) remains a leading cause of death worldwide. Early diagnosis is critical to protect innocent human lives. Computed tomography (CT) scans are one of the primary imaging modalities for lung cancer diagn…
Cancer ClassificationComputed Tomography (CT)Data AugmentationLung Cancer Diagnosis+1Comparative Analysis of Deep Learning Architectures for Breast Cancer Diagnosis Using the BreaKHis Dataset
Cancer is an extremely difficult and dangerous health problem because it manifests in so many different ways and affects so many different organs and tissues. The primary goal of this research was to evaluate deep learni…
Cancer ClassificationDeep LearningDiagnosticApplication of Machine Learning in Melanoma Detection and the Identification of 'Ugly Duckling' and Suspicious Naevi: A Review
Skin lesions known as naevi exhibit diverse characteristics such as size, shape, and colouration. The concept of an "Ugly Duckling Naevus" comes into play when monitoring for melanoma, referring to a lesion with distinct…
Cancer ClassificationDecision MakingSkin Cancer ClassificationDual-Activated Lightweight Attention ResNet50 for Automatic Histopathology Breast Cancer Image Classification
Automatic breast cancer classification in histopathology images is crucial for precise diagnosis and treatment planning. Recently, classification approaches based on the ResNet architecture have gained popularity for sig…
Cancer ClassificationClassificationimage-classificationImage ClassificationRevisiting Skin Tone Fairness in Dermatological Lesion Classification
Addressing fairness in lesion classification from dermatological images is crucial due to variations in how skin diseases manifest across skin tones. However, the absence of skin tone labels in public datasets hinders bu…
Cancer ClassificationClassificationFairnessLesion Classification+1SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification
Skin cancer is a treatable disease if discovered early. We provide a production-specific solution to the skin cancer classification problem that matches human performance in melanoma identification by training a vision t…
Cancer ClassificationClassificationCPUGPU+4A comprehensive review of deep learning in lung cancer
To provide the reader with a historical perspective on cancer classification approaches, we first discuss the fundamentals of the area of cancer diagnosis in this article, including the processes of cancer diagnosis and …
Cancer ClassificationClassificationDeep LearningDomain Transfer Through Image-to-Image Translation for Uncertainty-Aware Prostate Cancer Classification
Prostate Cancer (PCa) is a prevalent disease among men, and multi-parametric MRIs offer a non-invasive method for its detection. While MRI-based deep learning solutions have shown promise in supporting PCa diagnosis, acq…
Cancer ClassificationDeep LearningImage-to-Image Translation