Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Catheter-based interventions are widely used for the diagnosis and treatment of cardiac diseases. Recently, robotic catheters have attracted attention for their ability to improve precision and stability over conventional manual approaches. However, accurate modeling and control of soft robotic catheters remain challenging due to their complex, nonlinear behavior. The Koopman operator enables lift...
Rare diseases affect over 300 million people worldwide, yet patients often endure years-long diagnostic delays that limit timely intervention and trial opportunities. Computational rare disease recognition (RDR) remains constrained by knowledge resources that are often incomplete, heterogeneous, and dependent on extensive multi-disciplinary expert curation that cannot scale. Large language models ...
Genomic selection (GS) has become the core driving force in modern plant and animal breeding. However , state-of-the-art comprehensive GS tools often ...
Classical radiomic features are designed to quantify image appearance and intensity patterns. Compared with end-to-end deep learning (DL) models train...
Dataset Distillation (DD) compresses large datasets into compact synthetic ones that maintain training performance. However, current methods mainly ta...
Inhibition is a core cognitive control function whose competence is distributed across the population, with more extreme impairments in psychiatric co...
Large visual language models (VLMs) have shown strong multi-modal medical reasoning ability, but most operate as end-to-end black boxes, diverging fro...
Continuum robots possess high flexibility and redundancy, making them well suited for safe interaction in complex environments, yet their continuous d...
Existing image editing methods struggle to perceive where to edit, especially under complex scenes and nuanced spatial instructions. To address this i...
Differential privacy (DP)'s effect in medical imaging is typically evaluated only through end-to-end performance, leaving the mechanism of privacy-ind...
Abiotic stresses are primary constraints on global crop productivity, reducing yields by up to 80%. While traditional phenotypic sensing detects stres...
Small target detection in UAV imagery faces significant challenges such as scale variations, dense distribution, and the dominance of small targets. E...
Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain li...
Background: Objective Structured Clinical Examination (OSCE; Clinical Performance Examination [CPX] in South Korea) is a high-stakes assessment of cli...
Background: Although deep learning models have improved individual PET analysis, image processing and quantification tasks, end-to-end automation from...
While Vision-Language Models (VLMs) exhibit exceptional 2D visual understanding, their ability to comprehend and reason about 3D space--a cornerstone ...
Phenotyping is fundamental to rare disease diagnosis, but manual curation of structured phenotypes from clinical notes is labor-intensive and difficul...
Inverse problems in imaging are ill-posed, leading to infinitely many solutions consistent with the measurements due to the non-trivial null-space of ...
Visual loco-manipulation of arbitrary objects in the wild with humanoid robots requires accurate end-effector (EE) control and a generalizable underst...
Minutiae extraction, a fundamental stage in fingerprint recognition, is increasingly shifting toward deep learning. However, truly end-to-end methods ...