Transplantation

Introduction to Analytical Software Engineering Design Paradigm

As modern software systems expand in scale and complexity, the challenges associated with their modeling and formulation grow increasingly intricate. Traditional approaches often fall short in effectively addressing these complexities, particularly in tasks such as design pattern detection for maintenance and assessment, as well as code refactoring for optimization and long-term sustainability. ...

Adversarial Robustness for Unified Multi-Modal Encoders via Efficient Calibration

Recent unified multi-modal encoders align a wide range of modalities into a shared representation space, enabling diverse cross-modal tasks. Despite their impressive capabilities, the robustness of these models under adversarial perturbations remains underexplored, which is a critical concern for safety-sensitive applications. In this work, we present the first comprehensive study of adversarial...

Patient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy

Radiotherapy often involves a prolonged treatment period. During this time, patients may experience organ motion due to breathing and other physiolo...

A Training Framework for Optimal and Stable Training of Polynomial Neural Networks

By replacing standard non-linearities with polynomial activations, Polynomial Neural Networks (PNNs) are pivotal for applications such as privacy-pr...

Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data.

OBJECTIVES: In lung transplantation (LTx), a priority is assigned to each candidate on the waiting list. Our primary objective was to identify the key...

MOSAIC: A Multi-View 2.5D Organ Slice Selector with Cross-Attentional Reasoning for Anatomically-Aware CT Localization in Medical Organ Segmentation

Efficient and accurate multi-organ segmentation from abdominal CT volumes is a fundamental challenge in medical image analysis. Existing 3D segmenta...

On the Harmonisation of Time Series Data for the Optimisation of Machine Learning Using the Example of Rejection Prediction After Kidney Transplantation.

A significant risk following a kidney transplantation is graft loss. The Screen Reject Project has developed a Clinical Data Warehouse (CDWH) as a fou...

Privacy-Protecting Image Classification Within the Web Browser Using Deep Learning Models from Zenodo.

Integrating deep learning into clinical workflows for medical image analysis holds promise for improving diagnostic accuracy. However, strict data pri...

Patient Survival Prediction by Analyzing Pathological Images of Patients After Liver Transplantation.

Predicting whether a patient will develop cancer using nuclear features on pathological images is important for decision making regarding patient trea...

BoundarySeg:An Embarrassingly Simple Method To Boost Medical Image Segmentation Performance for Low Data Regimes

Obtaining large-scale medical data, annotated or unannotated, is challenging due to stringent privacy regulations and data protection policies. In a...

Real2Render2Real: Scaling Robot Data Without Dynamics Simulation or Robot Hardware

Scaling robot learning requires vast and diverse datasets. Yet the prevailing data collection paradigm-human teleoperation-remains costly and constr...

Single-cell RNA sequencing reveals immunological link between house dust mite allergy and childhood asthma.

Allergic asthma in children is typically associated with house dust mites (HDM) as the key allergen. Nevertheless, the diagnostic rate remains below 6...

Chaotic dynamics analysis and digital hardware design of the Izhikevich neuron model.

Neuromorphic hardware facilitates the fast and energy-efficient implementation of neural network-based artificial intelligence, making it particularly...

Fate-tox: fragment attention transformer for E(3)-equivariant multi-organ toxicity prediction.

Toxicity is a critical hurdle in drug development, often causing the late-stage failure of promising compounds. Existing computational prediction mode...

Development and Validation of Ultrasound Hemodynamic-based Prediction Models for Acute Kidney Injury After Renal Transplantation.

RATIONALE AND OBJECTIVES: Acute kidney injury (AKI) post-renal transplantation often has a poor prognosis. This study aimed to identify patients with ...

Engineering Conjugated Bridges in TPE-BT-Based Donor-Acceptor Molecules for Optimized Resistive Random Access Memory.

Four donor-acceptor (D-A) type organic small molecules, namely, 4,7-bis(4-(1,2,2-triphenylvinyl)phenyl)benzo[][1,2,5]thiadiazole(TPE-BT), 4,7-bis((4-(...

Ultrasound Report Generation with Multimodal Large Language Models for Standardized Texts

Ultrasound (US) report generation is a challenging task due to the variability of US images, operator dependence, and the need for standardized text...

Effectiveness of eHealth for Medication Adherence in Renal Transplant Recipients: Systematic Review and Meta-Analysis.

BACKGROUND: As the optimal treatment for end-stage renal disease, kidney transplantation has proven instrumental in enhancing patient survival and qua...

Severe community-acquired pneumonia (sCAP): advances in management and future directions.

Severe community-acquired pneumonia (sCAP) is a major global health challenge, with high morbidity and mortality, especially among patients requiring ...

Deep Learning-accelerated MRI in Body and Chest.

Deep learning reconstruction (DLR) provides an elegant solution for MR acceleration while preserving image quality. This advancement is crucial for bo...