Cover Image

Interpretable machine learning for time-to-event prediction in medicine and healthcare

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Baniecki, Hubert, Sobieski, Bartlomiej, Szatkowski, Patryk, Bombinski, Przemyslaw, Biecek, Przemyslaw
Format:	Preprint
Published:	2023
Subjects:	Computer Vision and Pattern Recognition Applications
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Birds look like cars: Adversarial analysis of intrinsically interpretable deep learning
by: Baniecki, Hubert, et al.
Published: (2025)

Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional Attributions
by: Sobieski, Bartlomiej, et al.
Published: (2026)

Global Counterfactual Directions
by: Sobieski, Bartlomiej, et al.
Published: (2024)

Underestimation of lung regions on chest X-ray segmentation masks assessed by comparison with total lung volume evaluated on computed tomography
by: Bombiński, Przemysław, et al.
Published: (2024)

Interpreting CLIP with Hierarchical Sparse Autoencoders
by: Zaigrajew, Vladimir, et al.
Published: (2025)

Adversarial attacks and defenses in explainable artificial intelligence: A survey
by: Baniecki, Hubert, et al.
Published: (2023)

Red-Teaming Segment Anything Model
by: Jankowski, Krzysztof, et al.
Published: (2024)

Rethinking Visual Counterfactual Explanations Through Region Constraint
by: Sobieski, Bartlomiej, et al.
Published: (2024)

SwordBench: Evaluating Orthogonality of Steering Image Representations
by: Zaigrajew, Vladimir, et al.
Published: (2026)

Aggregated Attributions for Explanatory Analysis of 3D Segmentation Models
by: Chrabaszcz, Maciej, et al.
Published: (2024)

Performance is not enough: the story told by a Rashomon quartet
by: Biecek, Przemyslaw, et al.
Published: (2023)

Explaining Similarity in Vision-Language Encoders with Weighted Banzhaf Interactions
by: Baniecki, Hubert, et al.
Published: (2025)

Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
by: Sobieski, Bartlomiej, et al.
Published: (2026)

Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI
by: Zaigrajew, Vladimir, et al.
Published: (2024)

Position: Do Not Explain Vision Models Without Context
by: Tomaszewska, Paulina, et al.
Published: (2024)

Does context matter in digital pathology?
by: Tomaszewska, Paulina, et al.
Published: (2024)

X-ray transferable polyrepresentation learning
by: Hryniewska-Guzik, Weronika, et al.
Published: (2025)

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts
by: Będkowski, Patryk, et al.
Published: (2025)

Multi-task learning for classification, segmentation, reconstruction, and detection on chest CT scans
by: Hryniewska-Guzik, Weronika, et al.
Published: (2023)

Swin SMT: Global Sequential Modeling in 3D Medical Image Segmentation
by: Płotka, Szymon, et al.
Published: (2024)

CNN-based explanation ensembling for dataset, representation and explanations evaluation
by: Hryniewska-Guzik, Weronika, et al.
Published: (2024)

Your CLIP has 164 dimensions of noise: Exploring the embeddings covariance eigenspectrum of contrastively pretrained vision-language transformers
by: Grzywaczewski, Jakub, et al.
Published: (2026)

Attributions All the Way Down? The Metagame of Interpretability
by: Baniecki, Hubert, et al.
Published: (2026)

Deep spatial context: when attention-based models meet spatial regression
by: Tomaszewska, Paulina, et al.
Published: (2024)

The Grammar of Interactive Explanatory Model Analysis
by: Baniecki, Hubert, et al.
Published: (2020)

NormEnsembleXAI: Unveiling the Strengths and Weaknesses of XAI Ensemble Techniques
by: Hryniewska-Guzik, Weronika, et al.
Published: (2024)

Multimodal Prototyping for cancer survival prediction
by: Song, Andrew H., et al.
Published: (2024)

Landcover classification and change detection using remote sensing and machine learning: a case study of Western Fiji
by: Gurjar, Yadvendra, et al.
Published: (2025)

Exploring selective image matching methods for zero-shot and few-sample unsupervised domain adaptation of urban canopy prediction
by: Francis, John, et al.
Published: (2024)

BARRIER: Bounded Activation Regions for Robust Information Erasure
by: Miksa, Jan, et al.
Published: (2026)

A comparative analysis of deep learning models for lung segmentation on X-ray images
by: Hryniewska-Guzik, Weronika, et al.
Published: (2024)

LINE: LLM-based Iterative Neuron Explanations for Vision Models
by: Zaigrajew, Vladimir, et al.
Published: (2026)

Deep Generative Models for Proton Zero Degree Calorimeter Simulations in ALICE, CERN
by: Będkowski, Patryk, et al.
Published: (2024)

Stop Marginalizing My Dreams: Model Inversion via Laplace Kernel for Continual Learning
by: Krukowski, Patryk, et al.
Published: (2026)

Remote sensing data imputation using deep learning for multispectral imagery
by: Liua, Shuang, et al.
Published: (2026)

A Stochastic-Geometrical Framework for Object Pose Estimation based on Mixture Models Avoiding the Correspondence Problem
by: Hoegele, Wolfgang
Published: (2023)

Parkinson gait modelling from an anomaly deep representation
by: Rangel, Edgar, et al.
Published: (2023)

Dynamic Atomic Column Detection in Transmission Electron Microscopy Videos via Ridge Estimation
by: Xu, Yuchen, et al.
Published: (2023)

AI Pose Analysis and Kinematic Profiling of Range-of-Motion Variations in Resistance Training
by: Diamant, Adam
Published: (2025)

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices
by: Zhang, Yuezhou, et al.
Published: (2025)