Transplantation

Automated measurement of hip-knee-ankle angle on the unilateral lower limb X-rays using deep learning.

Significant inherent extra-articular varus angulation is associated with abnormal postoperative hip-knee-ankle (HKA) angle. At present, HKA is manually measured by orthopedic surgeons and it increases the doctors' workload. To automatically determine HKA, a deep learning-based automated method for measuring HKA on the unilateral lower limb X-rays was developed and validated. This study retrospecti...

Systematic Identification of Molecular Targets and Pathways Related to Human Organ Level Toxicity.

The mechanisms leading to organ level toxicities are poorly understood. In this study, we applied an integrated approach to deduce the molecular targets and biological pathways involved in chemically induced toxicity for eight common human organ level toxicity end points (carcinogenicity, cardiotoxicity, developmental toxicity, hepatotoxicity, nephrotoxicity, neurotoxicity, reproductive toxicity, ...

Machine learning algorithm for early detection of end-stage renal disease.

BACKGROUND: End stage renal disease (ESRD) describes the most severe stage of chronic kidney disease (CKD), when patients need dialysis or renal trans...

Robot-assisted Transvaginal Single-site Sacrocolpopexy for Pelvic Organ Prolapse.

STUDY OBJECTIVE: To demonstrate stepwise techniques for the successful use of the laparoscopic single-site technique for safely performing transvagina...

Identification and validation of 174 COVID-19 vaccine candidate epitopes reveals low performance of common epitope prediction tools.

The outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune res...

Sodium butyrate protects against lipopolysaccharide-induced liver injury partially via the GPR43/ β-arrestin-2/NF-κB network.

BACKGROUND: Butyrate acts as a regulator in multiple inflammatory organ injuries. However, the role of butyrate in acute liver injury has not yet been...

Emerging use of machine learning and advanced technologies to assess red cell quality.

Improving blood product quality and patient outcomes is an accepted goal in transfusion medicine research. Thus, there is an urgent need to understand...

Risks of Muscle Atrophy in Patients with Malignant Lymphoma after Autologous Stem Cell Transplantation.

OBJECTIVE: Muscle atrophy is associated with autologous stem cell transplantation (ASCT)-related outcomes in patients with malignant lymphoma (ML). Ho...

Development and utility assessment of a machine learning bloodstream infection classifier in pediatric patients receiving cancer treatments.

BACKGROUND: Objectives were to build a machine learning algorithm to identify bloodstream infection (BSI) among pediatric patients with cancer and hem...

CT-ORG, a new dataset for multiple organ segmentation in computed tomography.

Despite the relative ease of locating organs in the human body, automated organ segmentation has been hindered by the scarcity of labeled training dat...

A 3D-2D Hybrid U-Net Convolutional Neural Network Approach to Prostate Organ Segmentation of Multiparametric MRI.

OBJECTIVE: Prostate cancer is the most commonly diagnosed cancer in men in the United States with more than 200,000 new cases in 2018. Multiparametric...

Circulating Neutrophil Extracellular Traps Signature for Identifying Organ Involvement and Response to Glucocorticoid in Adult-Onset Still's Disease: A Machine Learning Study.

Adult-onset Still's disease (AOSD) is an autoinflammatory disease with multisystem involvement. Early identification of patients with severe complicat...

Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tediou...

A deep learning approach for sepsis monitoring via severity score estimation.

BACKGROUND AND OBJECTIVE: Sepsis occurs in response to an infection in the body and can progress to a fatal stage. Detection and monitoring of sepsis ...

Deep Adversarial Training for Multi-Organ Nuclei Segmentation in Histopathology Images.

Nuclei mymargin segmentation is a fundamental task for various computational pathology applications including nuclei morphology analysis, cell type cl...

Multi-Organ Segmentation Over Partially Labeled Datasets With Multi-Scale Feature Abstraction.

Shortage of fully annotated datasets has been a limiting factor in developing deep learning based image segmentation algorithms and the problem become...

Personalized prediction of delayed graft function for recipients of deceased donor kidney transplants with machine learning.

Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) rem...

A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).

Machine learning techniques are widely used nowadays in the healthcare domain for the diagnosis, prognosis, and treatment of diseases. These technique...

Identifying gross post-mortem organ images using a pre-trained convolutional neural network.

Identifying organs/tissue and pathology on radiological and microscopic images can be performed using convolutional neural networks (CNN). However, th...

Decision-making in pediatric blunt solid organ injury: A deep learning approach to predict massive transfusion, need for operative management, and mortality risk.

BACKGROUND: The principal triggers for intervention in the setting of pediatric blunt solid organ injury (BSOI) are declining hemoglobin values and he...