Transplantation

RSNA 2023 Abdominal Trauma AI Challenge: Review and Outcomes.

Purpose To evaluate the performance of the winning machine learning models from the 2023 RSNA Abdominal Trauma Detection AI Challenge. Materials and Methods The competition was hosted on Kaggle and took place between July 26 and October 15, 2023. The multicenter competition dataset consisted of 4274 abdominal trauma CT scans, in which solid organs (liver, spleen, and kidneys) were annotated as hea...

Establishment and Validation of the Novel Necroptosis-related Genes for Predicting Stemness and Immunity of Hepatocellular Carcinoma Machine-learning Algorithm.

BACKGROUND: Necroptosis, a recently identified mechanism of programmed cell death, exerts significant influence on various aspects of cancer biology, including tumor cell proliferation, stemness, metastasis, and immunosuppression. However, the role of necroptosis-related genes (NRGs) in Hepatocellular Carcinoma (HCC) remains elusive.

Bayesian-optimized deep learning for identifying essential genes of mitophagy and fostering therapies to combat drug resistance in human cancers.

Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and de...

Artificial Intelligence-Assisted Matching of Human Postmortem Donors to Ocular Research Projects.

The scarcity of human ocular samples with short postmortem intervals (PMIs) is a significant issue in ophthalmic research and drug discovery. A contri...

Using Natural Language Processing and Machine Learning to classify the status of kidney allograft in Electronic Medical Records written in Spanish.

INTRODUCTION: Accurate identification of graft loss in Electronic Medical Records of kidney transplant recipients is essential but challenging due to ...

SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction

Sepsis is an organ dysfunction caused by a deregulated immune response to an infection. Early sepsis prediction and identification allow for timely ...

PQD: Post-training Quantization for Efficient Diffusion Models

Diffusionmodels(DMs)havedemonstratedremarkableachievements in synthesizing images of high fidelity and diversity. However, the extensive computation...

DPBridge: Latent Diffusion Bridge for Dense Prediction

Diffusion models demonstrate remarkable capabilities in capturing complex data distributions and have achieved compelling results in many generative...

Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentation

In medical image analysis, multi-organ semi-supervised segmentation faces challenges such as insufficient labels and low contrast in soft tissues. T...

MGAN-CRCM: A Novel Multiple Generative Adversarial Network and Coarse-Refinement Based Cognizant Method for Image Inpainting

Image inpainting is a widely used technique in computer vision for reconstructing missing or damaged pixels in images. Recent advancements with Gene...

Technological Progress and Obsolescence: Analyzing the Environmental Economic Impacts of MacBook Pro I/O Devices

This study investigates how the new release of MacBook Pro I/O devices affects the obsolescence of related accessories. We also explore how these ac...

Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for Foundation Models

The burgeoning field of foundation models necessitates advanced data processing mechanisms capable of harnessing vast valuable data with varied type...

DreamFit: Garment-Centric Human Generation via a Lightweight Anything-Dressing Encoder

Diffusion models for garment-centric human generation from text or image prompts have garnered emerging attention for their great application potent...

Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers

Whole-body hemodynamics simulators, which model blood flow and pressure waveforms as functions of physiological parameters, are now essential tools ...

Efficiently Solving Turn-Taking Stochastic Games with Extensive-Form Correlation

We study equilibrium computation with extensive-form correlation in two-player turn-taking stochastic games. Our main results are two-fold: (1) We g...

Performance evaluation of mixed-precision Runge-Kutta methods for the solution of partial differential equations

This work focuses on the numerical study of a recently published class of Runge-Kutta methods designed for mixed-precision arithmetic. We employ the...

Context-Aware Outlier Rejection for Robust Multi-View 3D Tracking of Similar Small Birds in An Outdoor Aviary

This paper presents a novel approach for robust 3D tracking of multiple birds in an outdoor aviary using a multi-camera system. Our method addresses...

MiniGPT-Pancreas: Multimodal Large Language Model for Pancreas Cancer Classification and Detection

Problem: Pancreas radiological imaging is challenging due to the small size, blurred boundaries, and variability of shape and position of the organ ...

Machine Learning Co-pilot for Screening of Organic Molecular Additives for Perovskite Solar Cells

Machine learning (ML) has been extensively employed in planar perovskite photovoltaics to screen effective organic molecular additives, while encoun...

Dynamic Adapter with Semantics Disentangling for Cross-lingual Cross-modal Retrieval

Existing cross-modal retrieval methods typically rely on large-scale vision-language pair data. This makes it challenging to efficiently develop a c...