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Survival Analysis

Survival Analysis is a branch of statistics focused on the study of time-to-event data, usually called survival times. This type of data appears in a wide range of applications such as failure times in mechanical systems, death times of patients in a clinical trial or duration of unemployment in a population. One of the main objectives of Survival Analysis is the estimation of the so-called survival function and the hazard function. If a random variable has density function $f$ and cumulative distribution function $F$, then its survival function $S$ is $1-F$, and its hazard $λ$ is $f/S$.

Source: Gaussian Processes for Survival Analysis

Image: Kvamme et al.

Papers

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Showing 51–75 of 472 papers

TitleStatusHype
CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learningCode0
Fairness in Survival Analysis: A Novel Conditional Mutual Information Augmentation Approach—0
SurvHive: a package to consistently access multiple survival-analysis packagesCode1
Context Matters: Query-aware Dynamic Long Sequence Modeling of Gigapixel ImagesCode0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift—0
Tackling Small Sample Survival Analysis via Transfer Learning: A Study of Colorectal Cancer PrognosisCode1
A Multi-Modal Deep Learning Framework for Pan-Cancer PrognosisCode0
Improved joint modelling of breast cancer radiomics features and hazard by image registration aided longitudinal CT data—0
Survival Analysis Revisited: Understanding and Unifying Poisson, Exponential, and Cox Models in Fall Risk Analysis—0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
SurvAttack: Black-Box Attack On Survival Models through Ontology-Informed EHR Perturbation—0
From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range Dependencies with Pixel-Mamba—0
Dynamic Entity-Masked Graph Diffusion Model for histopathological image Representation LearningCode0
Doubly Robust Conformalized Survival Analysis with Right-Censored DataCode0
SurvBETA: Ensemble-Based Survival Models Using Beran Estimators and Several Attention MechanismsCode0
Advancing clinical trial outcomes using deep learning and predictive modelling: bridging precision medicine and patient-centered care—0
A Differentially Private Kaplan-Meier Estimator for Privacy-Preserving Survival Analysis—0
A Versatile Influence Function for Data Attribution with Non-Decomposable Loss—0
EsurvFusion: An evidential multimodal survival fusion model based on Gaussian random fuzzy numbers—0
2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image ClassificationCode2
Enhanced Lung Cancer Survival Prediction using Semi-Supervised Pseudo-Labeling and Learning from Diverse PET/CT Datasets—0
RankByGene: Gene-Guided Histopathology Representation Learning Through Cross-Modal Ranking Consistency—0
Graph Domain Adaptation with Dual-branch Encoder and Two-level Alignment for Whole Slide Image-based Survival Prediction—0
Integrated Machine Learning and Survival Analysis Modeling for Enhanced Chronic Kidney Disease Risk StratificationCode0
Evidential time-to-event prediction with calibrated uncertainty quantification—0
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