Transplantation

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 knowledge, experience and technique. This work aims to develop an automated computed tomography (CT) multi-organ segmentation method for prostate cancer treatment planning.

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 characteristics are based on graft flow, but no researchers selected hemodynamic factors as the characteristics. The purpose of this paper is to study whether the introduction of hemodynamic factors will affect the performance of the prediction model. Transit time flow-meter (TTFM) waveforms and 1-year postoper...

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 targeted drug delivery (TDD). Particularly, stimu...

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 Information Extraction (IE) of low-prevalence concept...

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 reference databases. This restricts the possibility of dis...

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 antibiotherapy to the patient and reduce the presc...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ultrasound has been proposed to obtain real-time v...

Transplant nephrectomy with peritoneal window: Georgetown University experience.

OBJECTIVES: Transplant nephrectomy is a technically challenging procedure with high complication rates. Morbidity and mortality are mostly due to hemo...

Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration.

Convolutional neural networks (CNNs) have recently led to significant advances in automatic segmentations of anatomical structures in medical images, ...

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 their function is compromised in many blood disord...

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 different disease conditions. The heterogeneity of ...

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 visualize fully high-fidelity 3D / 4D organ geometric mo...

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 evaluation of its efficacy in individual organs. This pro...

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 opinions that has more answers like acceptance, rej...

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 neoplasms (e.g., pancreatic cyst), from abdominal CT ...

Predicting ideal outcome after pediatric liver transplantation: An exploratory study using machine learning analyses to leverage Studies of Pediatric Liver Transplantation Data.

Machine learning analyses allow for the consideration of numerous variables in order to accommodate complex relationships that would not otherwise be ...

Patient-based prediction algorithm of relapse after allo-HSCT for acute Leukemia and its usefulness in the decision-making process using a machine learning approach.

Although allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a curative therapy for high-risk acute leukemia (AL), some patients still r...

Evaluation and Identification of the Neuroprotective Compounds of Xiaoxuming Decoction by Machine Learning: A Novel Mode to Explore the Combination Rules in Traditional Chinese Medicine Prescription.

Xiaoxuming decoction (XXMD), a classic traditional Chinese medicine (TCM) prescription, has been used as a therapeutic in the treatment of stroke in c...

Optimization of the process variables of roller compaction, on the basis of granules characteristics (flow, mechanical strength, and disintegration behavior): an application of SeDeM-ODT expert system.

The objective of the study was application of SeDeM-ODT expert system for optimization of process variables for roller compaction and for the preparat...

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 severe acute pancreatitis (SAP). This study aimed t...