Papers Cancer Classification
“Cancer Classification” 태그가 달린 논문 260편 · 필터 해제
Enabling Data Diversity: Efficient Automatic Augmentation via Regularized Adversarial Training
Data augmentation has proved extremely useful by increasing training data variance to alleviate overfitting and improve deep neural networks' generalization performance. In medical image analysis, a well-designed augment…
Cancer ClassificationData AugmentationDiversityMedical Image Analysis+1Semi-Supervised Federated Peer Learning for Skin Lesion Classification
Globally, Skin carcinoma is among the most lethal diseases. Millions of people are diagnosed with this cancer every year. Sill, early detection can decrease the medication cost and mortality rate substantially. The recen…
Cancer ClassificationClassificationFederated LearningGeneral Classification+3An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification
Computer-aided skin cancer classification systems built with deep neural networks usually yield predictions based only on images of skin lesions. Despite presenting promising results, it is possible to achieve higher per…
Cancer ClassificationClassificationSkin Cancer ClassificationSkin Lesion ClassificationA Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation
Epigenetic alterations have an important role in the development of several types of cancer. Epigenetic studies generate a large amount of data, which makes it essential to develop novel models capable of dealing with la…
Cancer ClassificationClusteringDimensionality ReductionGeneral ClassificationComparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features
Cancer is responsible for millions of deaths worldwide every year. Although significant progress hasbeen achieved in cancer medicine, many issues remain to be addressed for improving cancer therapy.Appropriate cancer pat…
Cancer ClassificationA new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data
DNA methylation is a well-studied genetic modification that regulates gene transcription of Eukaryotes. Its alternations have been recognized as a significant component of cancer development. In this study, we use the DN…
Cancer ClassificationDiagnosticDimensionality Reductionfeature selectionAnalysis of Dimensional Influence of Convolutional Neural Networks for Histopathological Cancer Classification
Convolutional Neural Networks can be designed with different levels of complexity depending upon the task at hand. This paper analyzes the effect of dimensional changes to the CNN architecture on its performance on the t…
Cancer ClassificationGeneral ClassificationProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification
Lung cancer classification in screening computed tomography (CT) scans is one of the most crucial tasks for early detection of this disease. Many lives can be saved if we are able to accurately classify malignant/cancero…
Cancer ClassificationComputed Tomography (CT)General ClassificationLung Nodule ClassificationAttention Model Enhanced Network for Classification of Breast Cancer Image
Breast cancer classification remains a challenging task due to inter-class ambiguity and intra-class variability. Existing deep learning-based methods try to confront this challenge by utilizing complex nonlinear project…
Cancer ClassificationClassificationGeneral ClassificationTransfer learning with class-weighted and focal loss function for automatic skin cancer classification
Skin cancer is by far in top-3 of the world's most common cancer. Among different skin cancer types, melanoma is particularly dangerous because of its ability to metastasize. Early detection is the key to success in skin…
Cancer ClassificationDeep LearningGeneral ClassificationSkin Cancer Classification+1Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Classifiers in machine learning are often brittle when deployed. Particularly concerning are models with inconsistent performance on specific subgroups of a class, e.g., exhibiting disparities in skin cancer classificati…
Cancer ClassificationData AugmentationSkin Cancer ClassificationAuto-weighting for Breast Cancer Classification in Multimodal Ultrasound
Breast cancer is the most common invasive cancer in women. Besides the primary B-mode ultrasound screening, sonographers have explored the inclusion of Doppler, strain and shear-wave elasticity imaging to advance the dia…
Cancer ClassificationClassificationGeneral ClassificationDual Convolutional Neural Networks for Breast Mass Segmentation and Diagnosis in Mammography
Deep convolutional neural networks (CNNs) have emerged as a new paradigm for Mammogram diagnosis. Contemporary CNN-based computer-aided-diagnosis (CAD) for breast cancer directly extract latent features from input mammog…
Cancer ClassificationSegmentationDistractor-Aware Neuron Intrinsic Learning for Generic 2D Medical Image Classifications
Medical image analysis benefits Computer Aided Diagnosis (CADx). A fundamental analyzing approach is the classification of medical images, which serves for skin lesion diagnosis, diabetic retinopathy grading, and cancer …
Cancer ClassificationClassificationDiabetic Retinopathy GradingGeneral Classification+1Synthesizing lesions using contextual GANs improves breast cancer classification on mammograms
Data scarcity and class imbalance are two fundamental challenges in many machine learning applications to healthcare. Breast cancer classification in mammography exemplifies these challenges, with a malignancy rate of ar…
Cancer ClassificationData AugmentationGeneral ClassificationGenerative Adversarial NetworkCNN-based Approach for Cervical Cancer Classification in Whole-Slide Histopathology Images
Cervical cancer will cause 460 000 deaths per year by 2040, approximately 90% are Sub-Saharan African women. A constantly increasing incidence in Africa making cervical cancer a priority by the World Health Organization …
Cancer ClassificationGeneral ClassificationTransfer Learningwhole slide imagesConvolutional Neural Networks for Classifying Melanoma Images
In this work, we address the problem of skin cancer classification using convolutional neural networks. A lot of cancer cases early on are misdiagnosed leading to severe consequences including the death of patient. Also…
Cancer ClassificationSkin Cancer ClassificationTransfer LearningMulti-Task Learning in Histo-pathology for Widely Generalizable Model
In this work we show preliminary results of deep multi-task learning in the area of computational pathology. We combine 11 tasks ranging from patch-wise oral cancer classification, one of the most prevalent cancers in th…
Cancer ClassificationClassificationGeneral ClassificationInstance Segmentation+4Medical Image Enhancement Using Histogram Processing and Feature Extraction for Cancer Classification
MRI (Magnetic Resonance Imaging) is a technique used to analyze and diagnose the problem defined by images like cancer or tumor in a brain. Physicians require good contrast images for better treatment purpose as it conta…
Cancer ClassificationGeneral ClassificationImage EnhancementMedical Image EnhancementAdvanced Deep Learning Methodologies for Skin Cancer Classification in Prodromal Stages
Technology-assisted platforms provide reliable solutions in almost every field these days. One such important application in the medical field is the skin cancer classification in preliminary stages that need sensitive a…
Cancer ClassificationGeneral ClassificationRobust classificationSkin Cancer Classification