Transplantation

Supervised Machine Learning for Semi-Quantification of Extracellular DNA in Glomerulonephritis.

Glomerular cell death is a pathological feature of myeloperoxidase anti neutrophil cytoplasmic antibody associated vasculitis (MPO-AAV). Extracellular deoxyribonucleic acid (ecDNA) is released during different forms of cell death including apoptosis, necrosis, necroptosis, neutrophil extracellular traps (NETs) and pyroptosis. Measurement of this cell death is time consuming with several different ...

Evaluation of the ACS NSQIP surgical risk calculator in patients undergoing pelvic organ prolapse surgery.

INTRODUCTION AND HYPOTHESIS: The purpose of this study was to evaluate the accuracy of the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) surgical risk calculator in predicting postoperative complications in patients undergoing pelvic organ prolapse surgery.

Subsampled brain MRI reconstruction by generative adversarial neural networks.

A main challenge in magnetic resonance imaging (MRI) is speeding up scan time. Beyond improving patient experience and reducing operational costs, fas...

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

BACKGROUND: The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dial...

Deep Learning for Improved Risk Prediction in Surgical Outcomes.

The Norwood surgical procedure restores functional systemic circulation in neonatal patients with single ventricle congenital heart defects, but this ...

An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation.

The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental ex...

Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants.

The normalized difference vegetation index (NDVI) is widely used in remote sensing to monitor plant growth and chlorophyll levels. Usually, a multispe...

Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transpl...

Technological Innovation in Outpatient Assistance for Chronic Liver Disease and Liver Transplant Patients During the Coronavirus Disease Outbreak: A Method to Minimize Transmission.

The compatibility of theoretical frameworks with machine learning analyses in psychological research.

Supervised machine learning has been increasingly used in psychology and psychiatry research. Machine learning offers an important advantage over trad...

Results of Green Indocyanine in the Use of the R1T1 Robot as Aid in the Pre-operative Process of Hepatic Organ Transplant: Experiment in Wistar Rats.

Since the beginning of the history of transplants, numerous difficulties have been faced in the effective implementation of this therapeutic practice,...

CHEER: HierarCHical taxonomic classification for viral mEtagEnomic data via deep leaRning.

The fast accumulation of viral metagenomic data has contributed significantly to new RNA virus discovery. However, the short read size, complex compos...

Cochlear implant telemedicine: Remote fitting based on psychoacoustic self-tests and artificial intelligence.

This study aims to assess the feasibility of autonomous cochlear implant (CI) fitting by adult CI recipients based on psychoacoustic self-testing and...

Using Machine Learning to Predict Early Onset Acute Organ Failure in Critically Ill Intensive Care Unit Patients With Sickle Cell Disease: Retrospective Study.

BACKGROUND: Sickle cell disease (SCD) is a genetic disorder of the red blood cells, resulting in multiple acute and chronic complications, including p...

Discovering the hidden messages within cell trajectories using a deep learning approach for in vitro evaluation of cancer drug treatments.

We describe a novel method to achieve a universal, massive, and fully automated analysis of cell motility behaviours, starting from time-lapse microsc...

A Novel Radial Basis Neural Network-Leveraged Fast Training Method for Identifying Organs in MR Images.

We propose a new method for fast organ classification and segmentation of abdominal magnetic resonance (MR) images. Magnetic resonance imaging (MRI) i...

How to do it: a robotic kidney autotransplant.

We describe Australia's first reported case of robotic kidney autotransplantation for a complex renal artery aneurysm. It is potentially a safe, minim...

SPST-CNN: Spatial pyramid based searching and tagging of liver's intraoperative live views via CNN for minimal invasive surgery.

Laparoscopic liver surgery is challenging to perform because of compromised ability of the surgeon to localize subsurface anatomy due to minimal invas...

Machine Learning Classification Algorithms to Predict aGvHD following Allo-HSCT: A Systematic Review.

BACKGROUND:  The acute graft-versus-host disease (aGvHD) is the most important cause of mortality in patients receiving allogeneic hematopoietic stem ...

Predicting severe clinical events by learning about life-saving actions and outcomes using distant supervision.

Medical error is a leading cause of patient death in the United States. Among the different types of medical errors, harm to patients caused by doctor...