Transplantation

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

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Synthetic MRI-aided multi-organ segmentation on male pelvic CT using cycle consistent deep attention network.

BACKGROUND AND PURPOSE: Manual contouring is labor intensive, and subject to variations in operator ...

The influence of hemodynamics on graft patency prediction model based on support vector machine.

In the existing patency prediction model of coronary artery bypass grafting (CABG), the characterist...

Micro-nanorobots: important considerations when developing novel drug delivery platforms.

: There is growing emphasis on the development of bioinspired and biohybrid micro/nanorobots for the...

Comparing information extraction techniques for low-prevalence concepts: The case of insulin rejection by patients.

OBJECTIVE: To comparatively evaluate a range of Natural Language Processing (NLP) approaches for Inf...

Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid Peptide Sequencing Framework.

Typical analyses of mass spectrometry data only identify amino acid sequences that exist in referenc...

Fast and Accurate Bacterial Species Identification in Urine Specimens Using LC-MS/MS Mass Spectrometry and Machine Learning.

Fast identification of microbial species in clinical samples is essential to provide an appropriate ...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ...

Transplant nephrectomy with peritoneal window: Georgetown University experience.

OBJECTIVES: Transplant nephrectomy is a technically challenging procedure with high complication rat...

Machine learning predicts putative hematopoietic stem cells within large single-cell transcriptomics data sets.

Hematopoietic stem cells (HSCs) are an essential source and reservoir for normal hematopoiesis, and ...

Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.

INTRODUCTION: Machine learning has been increasingly used to develop predictive models to diagnose d...

DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network.

This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visual...

A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

One of the main problems of the decellularization technique is the subjectivity of the final evaluat...

Modeling of linear programming and extended TOPSIS in decision making problem under the framework of picture fuzzy sets.

Picture fuzzy sets (PFSs) are comparatively a new extension of fuzzy sets which describe the human o...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neo...

Development and validation of three machine-learning models for predicting multiple organ failure in moderately severe and severe acute pancreatitis.

BACKGROUND: Multiple organ failure (MOF) is a serious complication of moderately severe (MASP) and s...

Supervised Learning and Mass Spectrometry Predicts the Fate of Nanomaterials.

The surface of nanoparticles changes immediately after intravenous injection because blood proteins ...

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