Transplantation

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

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Extended Spatially Localized Perturbation GAN (eSLP-GAN) for Robust Adversarial Camouflage Patches.

Deep neural networks (DNNs), especially those used in computer vision, are highly vulnerable to adve...

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitativ...

Machine learning reveals mesenchymal breast carcinoma cell adaptation in response to matrix stiffness.

Epithelial-mesenchymal transition (EMT) and its reverse process, mesenchymal-epithelial transition (...

A deep learning approach to quantify auditory hair cells.

Hearing loss affects millions of people worldwide. Yet, there are still no curative therapies for se...

Study on the graft modification mechanism of macroporous silica gel surface based on silane coupling agent vinyl triethoxysilane.

In this research, the graft modification mechanism of coupling agent vinyl triethoxysilane (KH-151) ...

Robot-assisted Kidney Transplantation.

This paper describes robot-assisted kidney transplantation (RAKT) from a living donor. The robot is ...

An Unbiased Machine Learning Exploration Reveals Gene Sets Predictive of Allograft Tolerance After Kidney Transplantation.

Efforts at finding potential biomarkers of tolerance after kidney transplantation have been hindered...

Dual-Organ Transcriptomic Analysis of Rainbow Trout Infected With Through Co-Expression and Machine Learning.

is a major pathogen that causes a high mortality rate in trout farms. However, systemic responses t...

Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm.

One essential step in radiotherapy treatment planning is the organ at risk of segmentation in Comput...

Combining microfluidics with machine learning algorithms for RBC classification in rare hereditary hemolytic anemia.

Combining microfluidics technology with machine learning represents an innovative approach to conduc...

Assessing the utility of deep neural networks in predicting postoperative surgical complications: a retrospective study.

BACKGROUND: Early detection of postoperative complications, including organ failure, is pivotal in t...

State-of-the-art machine learning algorithms for the prediction of outcomes after contemporary heart transplantation: Results from the UNOS database.

PURPOSE: We sought to develop and validate machine learning (ML) models to increase the predictive a...

Interobserver variability in organ at risk delineation in head and neck cancer.

BACKGROUND: In radiotherapy inaccuracy in organ at risk (OAR) delineation can impact treatment plan ...

A machine learning approach for the prediction of overall deceased donor organ yield.

BACKGROUND: Optimizing organ yield (number of organs transplanted per donor) is a potentially modifi...

Robot-assisted kidney transplantation is a safe alternative approach for morbidly obese patients with end-stage renal disease.

BACKGROUND: Many centres deny obese patients with a body mass index (BMI) >35 access to kidney trans...

Genetic architecture of 11 organ traits derived from abdominal MRI using deep learning.

Cardiometabolic diseases are an increasing global health burden. While socioeconomic, environmental,...

Coronary vessel detection methods for organ-mounted robots.

BACKGROUND: HeartLander is a tethered robot walker that utilizes suction to adhere to the beating he...

In Vitro Assessment for Dose Preparation and Simulated Administration of Azithromycin Suspensions via Enteral Feeding Tubes.

Administration of medication via enteral feeding tubes (EFT) is common in cases where patients are u...

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