Transplantation

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

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Graph Neural Networks for Quantifying Compatibility Mechanisms in Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) involves complex compatibility mechanisms characterized by multi-component and multi-target interactions, which are challenging to quantify. To address this challenge, we applied graph artificial intelligence to develop a TCM multi-dimensional knowledge graph that bridges traditional TCM theory and modern biomedical science (https://zenodo.org/records/13763953 ...

Safe Text-to-Image Generation: Simply Sanitize the Prompt Embedding

In recent years, text-to-image (T2I) generation models have made significant progress in generating high-quality images that align with text descriptions. However, these models also face the risk of unsafe generation, potentially producing harmful content that violates usage policies, such as explicit material. Existing safe generation methods typically focus on suppressing inappropriate content...

High-dimensional Immune Profiles and Machine Learning May Predict Acute Myeloid Leukemia Relapse Early following Transplant.

Identification of early immune signatures associated with acute myeloid leukemia (AML) relapse following hematopoietic stem cell transplant (HSCT) is ...

Nov 15 2024 39373568
Artificial intelligence enabled interpretation of ECG images to predict hematopoietic cell transplantation toxicity.

Artificial intelligence (AI)-enabled interpretation of electrocardiogram (ECG) images (AI-ECGs) can identify patterns predictive of future adverse car...

Nov 12 2024 39158065
scMEDAL for the interpretable analysis of single-cell transcriptomics data with batch effect visualization using a deep mixed effects autoencoder

scRNA-seq data has the potential to provide new insights into cellular heterogeneity and data acquisition; however, a major challenge is unraveling ...

Elucidating the cellular determinants of the end-systolic pressure-volume relationship of the heart via computational modelling

The left ventricular end-systolic pressure-volume relationship (ESPVr) is a key indicator of cardiac contractility. Despite its established importan...

Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the FLARE22 challenge.

Deep learning has shown great potential to automate abdominal organ segmentation and quantification. However, most existing algorithms rely on expert ...

Nov 1 2024 39455194
Machine learning-driven in-hospital mortality prediction in HIV/AIDS patients with infection: a single-centred retrospective study.

() is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocompromised populations, especially transplant and HI...

Nov 1 2024 39606806
Xeno-learning: knowledge transfer across species in deep learning-based spectral image analysis

Novel optical imaging techniques, such as hyperspectral imaging (HSI) combined with machine learning-based (ML) analysis, have the potential to revo...

A discrete event simulator for policy evaluation in liver allocation in Eurotransplant

We present the ELAS simulator, a discrete event simulator built for the Eurotransplant (ET) Liver Allocation System (ELAS). Eurotransplant uses ELAS...

Neural Contrast: Leveraging Generative Editing for Graphic Design Recommendations

Creating visually appealing composites requires optimizing both text and background for compatibility. Previous methods have focused on simple desig...

Decoding Style: Efficient Fine-Tuning of LLMs for Image-Guided Outfit Recommendation with Preference

Personalized outfit recommendation remains a complex challenge, demanding both fashion compatibility understanding and trend awareness. This paper p...

Parallel Reduced Order Modeling for Digital Twins using High-Performance Computing Workflows

The integration of reduced-order models (ROMs) with high-performance computing (HPC) is critical for developing digital twins, particularly for real...

VQ-DeepVSC: A Dual-Stage Vector Quantization Framework for Video Semantic Communication

In response to the rapid growth of global videomtraffic and the limitations of traditional wireless transmission systems, we propose a novel dual-st...

NeoaPred: a deep-learning framework for predicting immunogenic neoantigen based on surface and structural features of peptide-human leukocyte antigen complexes.

MOTIVATION: Neoantigens, derived from somatic mutations in cancer cells, can elicit anti-tumor immune responses when presented to autologous T cells b...

Sep 2 2024 39276157
From organs to algorithms: Redefining cancer classification in the age of artificial intelligence.

Traditional cancer classification based on organ of origin and histology is increasingly at odds with precision oncology. Tumors in different organs c...

Sep 1 2024 39206604
Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to cur...

Sep 1 2024 39294741
Automatic Tumor Cellularity Measurement: AI-Based Pipeline for Multi-Organ Pathology Imaging.

Tumor Cellularity (TC) is an important metric for assessing organ tumor burden. However, manual cell counting is not feasible due to large volumes of ...

Aug 22 2024 39176828
In-Memory Computing Architecture for Efficient Hardware Security

This paper presents an innovative approach utilizing in-memory computing (IMC) for the development and integration of AES (Advanced Encryption Stand...

Standard compliant video coding using low complexity, switchable neural wrappers

The proliferation of high resolution videos posts great storage and bandwidth pressure on cloud video services, driving the development of next-gene...

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