Transplantation

Latest AI and machine learning research in transplantation for healthcare professionals.

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Leveraging Artificial Intelligence to Assess Perceived Age and Donor Facial Resemblance After Face Transplantation.

PURPOSE: A major concern for patients undergoing facial transplantation relates to postoperative appearance. This study leverages artificial intelligence (AI) visual analysis software to provide an objective assessment of perceived age and degree of resemblance to the donor.

Apr 1 2025 40117511

A Neural Network Finite Element Trileaflet Heart Valve Model Incorporating Multi-Body Contact.

The use of patient-specific computational modeling of cardiovascular diseases has become increasingly popular to improve patient standard of care. Most simulation approaches currently utilize the finite element method (FEM), which is very well established and succeeds in producing high-fidelity results. However, it remains too slow for use in clinical settings, especially when many-query solutions...

Apr 1 2025 40210840
Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.

BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to...

Apr 1 2025 40245174
Thinking Longer, Not Larger: Enhancing Software Engineering Agents via Scaling Test-Time Compute

Recent advancements in software engineering agents have demonstrated promising capabilities in automating program improvements. However, their relia...

Internal Organ Localization Using Depth Images

Automated patient positioning is a crucial step in streamlining MRI workflows and enhancing patient throughput. RGB-D camera-based systems offer a p...

uHAF: a unified hierarchical annotation framework for cell type standardization and harmonization.

SUMMARY: In single-cell transcriptomics, inconsistent cell type annotations due to varied naming conventions and hierarchical granularity impede data ...

Mar 29 2025 40172934
Neural Identification of Feedback-Stabilized Nonlinear Systems

Neural networks have demonstrated remarkable success in modeling nonlinear dynamical systems. However, identifying these systems from closed-loop ex...

MO-CTranS: A unified multi-organ segmentation model learning from multiple heterogeneously labelled datasets

Multi-organ segmentation holds paramount significance in many clinical tasks. In practice, compared to large fully annotated datasets, multiple smal...

Hybrid Time-Domain Behavior Model Based on Neural Differential Equations and RNNs

Nonlinear dynamics system identification is crucial for circuit emulation. Traditional continuous-time domain modeling approaches have limitations i...

Divide to Conquer: A Field Decomposition Approach for Multi-Organ Whole-Body CT Image Registration

Image registration is an essential technique for the analysis of Computed Tomography (CT) images in clinical practice. However, existing methodologi...

Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks

Recent advances in deep thinking models have demonstrated remarkable reasoning capabilities on mathematical and coding tasks. However, their effecti...

OCEP: An Ontology-Based Complex Event Processing Framework for Healthcare Decision Support in Big Data Analytics

The exponential expansion of real-time data streams across multiple domains needs the development of effective event detection, correlation, and dec...

Online Reasoning Video Segmentation with Just-in-Time Digital Twins

Reasoning segmentation (RS) aims to identify and segment objects of interest based on implicit text queries. As such, RS is a catalyst for embodied ...

Semi-supervised learning for marine anomaly detection on board satellites

Aquatic bodies face numerous environmental threats caused by several marine anomalies. Marine debris can devastate habitats and endanger marine life...

The Greatest Good Benchmark: Measuring LLMs' Alignment with Utilitarian Moral Dilemmas

The question of how to make decisions that maximise the well-being of all persons is very relevant to design language models that are beneficial to ...

Compositional Caching for Training-free Open-vocabulary Attribute Detection

Attribute detection is crucial for many computer vision tasks, as it enables systems to describe properties such as color, texture, and material. Cu...

An End-to-End GSM/SMS Encrypted Approach for Smartphone Employing Advanced Encryption Standard(AES)

Encryption is crucial for securing sensitive data during transmission over networks. Various encryption techniques exist, such as AES, DES, and RC4,...

EvAnimate: Event-conditioned Image-to-Video Generation for Human Animation

Conditional human animation transforms a static reference image into a dynamic sequence by applying motion cues such as poses. These motion cues are...

Hiding Images in Diffusion Models by Editing Learned Score Functions

Hiding data using neural networks (i.e., neural steganography) has achieved remarkable success across both discriminative classifiers and generative...

Why do Opinions and Actions Diverge? A Dynamic Framework to Explore the Impact of Subjective Norms

Socio-psychological studies have identified a common phenomenon where an individual's public actions do not necessarily coincide with their private ...

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