Papers Survival Prediction
“Survival Prediction” 태그가 달린 논문 233편 · 필터 해제
Adaptive Prototype Learning for Multimodal Cancer Survival Analysis
Leveraging multimodal data, particularly the integration of whole-slide histology images (WSIs) and transcriptomic profiles, holds great promise for improving cancer survival prediction. However, excessive redundancy in …
Survival AnalysisSurvival PredictionCrossFusion: A Multi-Scale Cross-Attention Convolutional Fusion Model for Cancer Survival Prediction
Cancer survival prediction from whole slide images (WSIs) is a challenging task in computational pathology due to the large size, irregular shape, and high granularity of the WSIs. These characteristics make it difficult…
PrognosisSurvival Predictionwhole slide imagesA Data-Efficient Pan-Tumor Foundation Model for Oncology CT Interpretation
Artificial intelligence-assisted imaging analysis has made substantial strides in tumor diagnosis and management. Here we present PASTA, a pan-tumor CT foundation model that achieves state-of-the-art performance on 45 of…
Lesion SegmentationStructured Report GenerationSurvival PredictionTransfer LearningMolecular-driven Foundation Model for Oncologic Pathology
Foundation models are reshaping computational pathology by enabling transfer learning, where models pre-trained on vast datasets can be adapted for downstream diagnostic, prognostic, and therapeutic response tasks. Despi…
BenchmarkingDiagnosticmodelSurvival Prediction+2ICFNet: Integrated Cross-modal Fusion Network for Survival Prediction
Survival prediction is a crucial task in the medical field and is essential for optimizing treatment options and resource allocation. However, current methods often rely on limited data modalities, resulting in suboptima…
Decision MakingSurvival Predictionwhole slide imagesRobust Multimodal Survival Prediction with Conditional Latent Differentiation Variational AutoEncoder
The integrative analysis of histopathological images and genomic data has received increasing attention for survival prediction of human cancers. However, the existing studies always hold the assumption that full mod…
Survival Predictionwhole slide imagesDistilled Prompt Learning for Incomplete Multimodal Survival Prediction
The integration of multimodal data including pathology images and gene profiles is widely applied in precise survival prediction. Despite recent advances in multimodal survival models, collecting complete modalities …
PredictionPrompt LearningSurvival PredictionFrom Histopathology Images to Cell Clouds: Learning Slide Representations with Hierarchical Cell Transformer
It is clinically crucial and potentially very beneficial to be able to analyze and model directly the spatial distributions of cells in histopathology whole slide images (WSI). However, most existing WSI datasets lack ce…
Survival Predictionwhole slide imagesMultimodal Integration of Longitudinal Noninvasive Diagnostics for Survival Prediction in Immunotherapy Using Deep Learning
Purpose: Immunotherapies have revolutionized the landscape of cancer treatments. However, our understanding of response patterns in advanced cancers treated with immunotherapy remains limited. By leveraging routinely col…
Survival PredictionMultimodal Outer Arithmetic Block Dual Fusion of Whole Slide Images and Omics Data for Precision Oncology
The integration of DNA methylation data with a Whole Slide Image (WSI) offers significant potential for enhancing the diagnostic precision of central nervous system (CNS) tumor classification in neuropathology. While exi…
DiagnosticMultiple Instance LearningSurvival Predictionwhole slide imagesEnhanced Lung Cancer Survival Prediction using Semi-Supervised Pseudo-Labeling and Learning from Diverse PET/CT Datasets
Objective: This study explores a semi-supervised learning (SSL), pseudo-labeled strategy using diverse datasets to enhance lung cancer (LCa) survival predictions, analyzing Handcrafted and Deep Radiomic Features (HRF/DRF…
Hybrid Machine LearningSurvival AnalysisSurvival PredictionGraph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction
In recent years, histopathological whole slide image (WSI)- based survival analysis has attracted much attention in medical image analysis. In practice, WSIs usually come from different hospitals or laboratories, which c…
Domain AdaptationGRAPH DOMAIN ADAPTATIONMedical Image AnalysisSurvival Analysis+1Look a Group at Once: Multi-Slide Modeling for Survival Prediction
Survival prediction is a critical task in pathology. In clinical practice, pathologists often examine multiple cases, leveraging a broader spectrum of cancer phenotypes to enhance pathological assessment. Despite signifi…
Survival PredictionxCG: Explainable Cell Graphs for Survival Prediction in Non-Small Cell Lung Cancer
Understanding how deep learning models predict oncology patient risk can provide critical insights into disease progression, support clinical decision-making, and pave the way for trustworthy and data-driven precision me…
Decision MakingSurvival PredictionPathoGen-X: A Cross-Modal Genomic Feature Trans-Align Network for Enhanced Survival Prediction from Histopathology Images
Accurate survival prediction is essential for personalized cancer treatment. However, genomic data - often a more powerful predictor than pathology data - is costly and inaccessible. We present the cross-modal genomic fe…
PredictionPrognosisSurvival PredictionEnhanced Survival Prediction in Head and Neck Cancer Using Convolutional Block Attention and Multimodal Data Fusion
Accurate survival prediction in head and neck cancer (HNC) is essential for guiding clinical decision-making and optimizing treatment strategies. Traditional models, such as Cox proportional hazards, have been widely use…
Decision MakingPredictionSurvival PredictionToward Conditional Distribution Calibration in Survival Prediction
Survival prediction often involves estimating the time-to-event distribution from censored datasets. Previous approaches have focused on enhancing discrimination and marginal calibration. In this paper, we highlight the …
Conformal PredictionDecision MakingPredictionSurvival PredictionHACSurv: A Hierarchical Copula-Based Approach for Survival Analysis with Dependent Competing Risks
In survival analysis, subjects often face competing risks; for example, individuals with cancer may also suffer from heart disease or other illnesses, which can jointly influence the prognosis of risks and censoring. Tra…
PrognosisSurvival AnalysisSurvival PredictionSlide-based Graph Collaborative Training for Histopathology Whole Slide Image Analysis
The development of computational pathology lies in the consensus that pathological characteristics of tumors are significant guidance for cancer diagnostics. Most existing research focuses on the inner-contextual informa…
Multiple Instance LearningRepresentation LearningSurvival PredictionForecasting Disease Progression with Parallel Hyperplanes in Longitudinal Retinal OCT
Predicting future disease progression risk from medical images is challenging due to patient heterogeneity, and subtle or unknown imaging biomarkers. Moreover, deep learning (DL) methods for survival analysis are suscept…
Prediction IntervalsSurvival AnalysisSurvival Prediction