Care of terminally ill / Palliative care

MacNet: An End-to-End Manifold-Constrained Adaptive Clustering Network for Interpretable Whole Slide Image Classification

Whole slide images (WSIs) are the gold standard for pathological diagnosis and sub-typing. Current main-stream two-step frameworks employ offline feature encoders trained without domain-specific knowledge. Among them, attention-based multiple instance learning (MIL) methods are outcome-oriented and offer limited interpretability. Clustering-based approaches can provide explainable decision-making ...

CoPE-VideoLM: Codec Primitives For Efficient Video Language Models

Video Language Models (VideoLMs) empower AI systems to understand temporal dynamics in videos. To fit to the maximum context window constraint, current methods use keyframe sampling which can miss both macro-level events and micro-level details due to the sparse temporal coverage. Furthermore, processing full images and their tokens for each frame incurs substantial computational overhead. To addr...

Prototype-driven fusion of pathology and spatial transcriptomics for interpretable survival prediction

Whole slide images (WSIs) enable weakly supervised prognostic modeling via multiple instance learning (MIL). Spatial transcriptomics (ST) preserves in...

Ctrl&Shift: High-Quality Geometry-Aware Object Manipulation in Visual Generation

Object-level manipulation, relocating or reorienting objects in images or videos while preserving scene realism, is central to film post-production, A...

MetaphorStar: Image Metaphor Understanding and Reasoning with End-to-End Visual Reinforcement Learning

Metaphorical comprehension in images remains a critical challenge for Nowadays AI systems. While Multimodal Large Language Models (MLLMs) excel at bas...

Structural phenotypes of osteoarthritis are clinically and genetically distinct: findings from 59,539 UK Biobank participants

OBJECTIVES Osteoarthritis is a heterogeneous disease, with diverse structural patterns likely reflecting distinct genetic drivers. Robust, data-driven...

AD$^2$: Analysis and Detection of Adversarial Threats in Visual Perception for End-to-End Autonomous Driving Systems

End-to-end autonomous driving systems have achieved significant progress, yet their adversarial robustness remains largely underexplored. In this work...

Model-Driven Hybrid AI Framework for End-to-End Autonomous Decision-Making in Drug Development

Decision-making in drug development spans heterogeneous stages from molecular design to clinical optimization, yet computer-aided workflows across sta...

Full end-to-end diagnostic workflow automation of 3D OCT via foundation model-driven AI for retinal diseases

Optical coherence tomography (OCT) has revolutionized retinal disease diagnosis with its high-resolution and three-dimensional imaging nature, yet its...

End-to-end reconstruction of OCT optical properties and speckle-reduced structural intensity via physics-based learning

Inverse scattering in optical coherence tomography (OCT) seeks to recover both structural images and intrinsic tissue optical properties, including re...

Developing and externally validating machine learning models to forecast short-term risk of ventilator-associated pneumonia

Purpose: Ventilator-associated pneumonia (VAP) remains one of the most serious hospital-acquired infections in the intensive care unit (ICU), with hig...

OCRVerse: Towards Holistic OCR in End-to-End Vision-Language Models

The development of large vision language models drives the demand for managing, and applying massive amounts of multimodal data, making OCR technology...

ChartE$^{3}$: A Comprehensive Benchmark for End-to-End Chart Editing

Charts are a fundamental visualization format for structured data analysis. Enabling end-to-end chart editing according to user intent is of great pra...

Li-ViP3D++: Query-Gated Deformable Camera-LiDAR Fusion for End-to-End Perception and Trajectory Prediction

End-to-end perception and trajectory prediction from raw sensor data is one of the key capabilities for autonomous driving. Modular pipelines restrict...

NuiWorld: Exploring a Scalable Framework for End-to-End Controllable World Generation

World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main...

VC-Bench: Pioneering the Video Connecting Benchmark with a Dataset and Evaluation Metrics

While current video generation focuses on text or image conditions, practical applications like video editing and vlogging often need to seamlessly co...

SqueakPose Studio: An end-to-end platform for pose estimation and real-time edge-AI deployment

Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflo...

End-to-end deep learning versus machine learning for biomarker discovery in cancer genomes

Background: Accurate determination of genomic biomarkers from tumor sequencing is fundamental to precision oncology, informing disease classification ...

Learning temporal embeddings from electronic health records of chronic kidney disease patients

We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations wit...

NanoSimFormer: An end-to-end Transformer-based simulator for nanopore sequencing signal data

Nanopore sequencing has achieved a new standard of accuracy with the advent of R10.4.1 flow cell and high-performance Transformer-based basecalling mo...