Papers with Code 아카이브

Cancer Classification

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

0

평가표

1

보존된 평가 기록

2

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/2313595986/smilecode

공식 코드

Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound

https://github.com/BreastGAN/augmentation

공식 코드

Adversarial Augmentation for Enhancing Classification of Mammography Images

https://github.com/HazyResearch/model-patching

공식 코드

Model Patching: Closing the Subgroup Performance Gap with Data Augmentation

https://github.com/KyleYoung1997/DNNorDermatologist

공식 코드

Deep neural network or dermatologist?

https://github.com/MIDA-group/OralScreen

공식 코드

A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images

https://github.com/Mukaffi28/Explainable-AI-for-Lung-and-Colon-Cancer-Classification

공식 코드

Exploring Explainable AI Techniques for Improved Interpretability in Lung and Colon Cancer Classification

https://github.com/Paige-AI/paige-ml-sdk

공식 코드

Virchow: A Million-Slide Digital Pathology Foundation Model

https://github.com/WkEEn/PAMA

공식 코드

Pan-cancer Histopathology WSI Pre-training with Position-aware Masked Autoencoder

https://github.com/alceubissoto/gan-skin-lesion

공식 코드

Skin Lesion Synthesis with Generative Adversarial Networks

https://github.com/ameliajimenez/curriculum-federated-learning

공식 코드

Memory-aware curriculum federated learning for breast cancer classification

https://github.com/annkristinbalve/Interpretable_Breast_Cancer_Classification

공식 코드

Interpretable breast cancer classification using CNNs on mammographic images

https://github.com/ayushroy2001/wagf-fusion

공식 코드

A Wavelet Guided Attention Module for Skin Cancer Classification with Gradient-based Feature Fusion

https://github.com/biomedia-repo/tseml

공식 코드

TSEML: A task-specific embedding-based method for few-shot classification of cancer molecular subtypes

https://github.com/catai9/cancer-net-sca-synth

공식 코드

Cancer-Net SCa-Synth: An Open Access Synthetically Generated 2D Skin Lesion Dataset for Skin Cancer Classification

https://github.com/datct00/Beyond-Traditional-Approaches-Multi-Task-Network-for-Breast-Ultrasound-Diagnosis

공식 코드

Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound Diagnosis

https://github.com/digitalhealthcarelab/25multimodalfoundationmodel

공식 코드

MEDFORM: A Foundation Model for Contrastive Learning of CT Imaging and Clinical Numeric Data in Multi-Cancer Analysis

https://github.com/elianastasio/minigpt-pancreas

공식 코드

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection

https://github.com/fitushar/AI-in-Lung-Health-Benchmarking-Detection-and-Diagnostic-Models-Across-Multiple-CT-Scan-Datasets

공식 코드

AI in Lung Health: Benchmarking Detection and Diagnostic Models Across Multiple CT Scan Datasets

https://github.com/hawaii-ai/bus-cbm

공식 코드

Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound

https://github.com/hhi-aml/histobenchmark

공식 코드

From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathology

https://github.com/isha-67/cervicalcancerstudy

공식 코드

Explainable Contrastive and Cost-Sensitive Learning for Cervical Cancer Classification

https://github.com/ispamm/phbreast

공식 코드

Multi-View Hypercomplex Learning for Breast Cancer Screening

https://github.com/ispras/mammo_crop

공식 코드

MamT$^4$: Multi-view Attention Networks for Mammography Cancer Classification

https://github.com/lhy1007/m3c2

공식 코드

Joint Modelling Histology and Molecular Markers for Cancer Classification

https://github.com/longman-stan/skindistilvit

공식 코드

SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification

https://github.com/majid9418/Breast-Tumor-Classification-Histopathological

공식 코드

Breast Tumor Classification Using EfficientNet Deep Learning Model

https://github.com/martabuetas/enhancingbreastcancerdiagnosis

공식 코드

Mitigating annotation shift in cancer classification using single image generative models

https://github.com/menggersherry/gene-moe

공식 코드

Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information

https://github.com/nabavilab/multimodal-gnn-for-cancer-subtype-clasification

공식 코드

A Multimodal Graph Neural Network Framework of Cancer Molecular Subtype Classification

https://github.com/prithuls/mv-swin-t

공식 코드

MV-Swin-T: Mammogram Classification with Multi-view Swin Transformer

https://github.com/saniaesk/Breast-Cancer-Classification

공식 코드

Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study

https://github.com/schuture/meta-uscl

공식 코드

Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive Learning

https://github.com/skrantidatta/Attention-based-Skin-Cancer-Classification

공식 코드

Soft-Attention Improves Skin Cancer Classification Performance

https://github.com/tamirshor7/latents-guided-thermography

공식 코드

Leveraging Latents for Efficient Thermography Classification and Segmentation

https://github.com/tbdair/fedperlv1.0

공식 코드

Semi-Supervised Federated Peer Learning for Skin Lesion Classification

https://github.com/tkalbl/revisitingskintonefairness

공식 코드

Revisiting Skin Tone Fairness in Dermatological Lesion Classification

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.