End Stage Renal Disease

Comparison of Open and Robot-Assisted Kidney Transplantation in terms of Perioperative and Postoperative Outcomes.

BACKGROUND: The gold standard treatment method for end-stage renal disease (ESRD) is renal transplantation (RT). RT can be done with open or minimally invasive surgical methods. We aimed to compare the outcomes between patients who underwent robot-assisted renal transplantation (RART) and open renal transplantation (ORT).

A non-invasive approach to monitor anemia during long-duration spaceflight with retinal fundus images and deep learning.

During spaceflight, astronauts can experience significantly higher levels of hemolysis. With future space missions exposing astronauts to longer periods of microgravity, such as missions to Mars, there will be a need to better understand this phenomenon. We have proposed that retinal fundus photography and deep learning may be utilized to help further understand this microgravity-induced, anemic p...

A visual deep learning model to predict abnormal versus normal parathyroid glands using intraoperative autofluorescence signals.

BACKGROUND: Previous work demonstrated that abnormal versus normal parathyroid glands (PGs) exhibit different patterns of autofluorescence, with forme...

Profiling of 35 Cases of Hb S/Hb E (: c.20A>T/: c.79G>a), Disease and Association with α-Thalassemia and β-Globin Gene Cluster Haplotypes from Odisha, India.

Hb S/Hb E (: c.20A>T/: c.79G>A) is an uncommon variant of sickle cell disease resulting from coinheritance of Hb S and Hb E. Clinico-hematological and...

The role of artificial intelligence in pancreatic surgery: a systematic review.

Artificial intelligence (AI), including machine learning (ML), is being slowly incorporated in medical practice, to provide a more precise and persona...

Deep learning-based detection of parathyroid adenoma by Tc-MIBI scintigraphy in patients with primary hyperparathyroidism.

OBJECTIVE: It is important to detect parathyroid adenomas by parathyroid scintigraphy with 99m-technetium sestamibi (Tc-MIBI) before surgery. This stu...

Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it...

Anemia or other comorbidities? using machine learning to reveal deeper insights into the drivers of acute coronary syndromes in hospital admitted patients.

Acute coronary syndromes (ACS) are a leading cause of deaths worldwide, yet the diagnosis and treatment of this group of diseases represent a signific...

Ranking patients on the kidney transplant waiting list based on fuzzy inference system.

BACKGROUND: Kidney transplantation is the best treatment for people with End-Stage Renal Disease (ESRD). Kidney allocation is the most important chall...

Construction of a prediction model for drug removal rate in hemodialysis based on chemical structures.

In designing drug dosing for hemodialysis patients, the removal rate (RR) of the drug by hemodialysis is important. However, acquiring the RR is diffi...

Joint Deep-Learning-Enabled Impact of Holistic Care on Line Coagulation in Hemodialysis.

In order to investigate the impact of holistic care on line coagulation and safety in hemodialysis and to address limitations of the conventional ultr...

Comparison of a Kidney Replacement Therapy Risk Score Developed in Kaiser Permanente Northwest vs Estimated Glomerular Filtration Rate in Advanced Chronic Kidney Disease Using Decision Curve Analysis.

INTRODUCTION: Use of kidney replacement therapy (KRT) prediction models for guiding arteriovenous fistula (AVF) referrals in advanced chronic kidney d...

Comparative Analysis for Prediction of Kidney Disease Using Intelligent Machine Learning Methods.

Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage re...

CT Image Feature Diagnosis on the Basis of Deep Learning Algorithm for Preoperative Patients and Complications of Transcatheter Aortic Valve Implantation.

This work was aimed to explore the role of CT angiography information provided by deep learning algorithm in the diagnosis and complications of the di...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was ...

Predicting completion of clinical trials in pregnant women: Cox proportional hazard and neural network models.

This study aimed to develop a model for predicting the completion of clinical trials involving pregnant women using the Cox proportional hazard model ...

A deep learning method for counting white blood cells in bone marrow images.

BACKGROUND: Differentiating and counting various types of white blood cells (WBC) in bone marrow smears allows the detection of infection, anemia, and...

PEGylated ethyl cellulose micelles as a nanocarrier for drug delivery.

Natural polymers provide a better alternative to synthetic polymers in the domain of drug delivery systems (DDSs) because of their renewability, bioco...

Robotic Puboprostatic Fistula Repair with Holmium Laser Pubic Debridement.

INTRODUCTION AND OBJECTIVE: Urosymphyseal fistula (UF) with osteomyelitis most commonly occurs as a result of prostate cancer and benign prostate hype...

Deep Learning-Based Magnetic Resonance Imaging Features in Diagnosis of Perianal Abscess and Fistula Formation.

There was an investigation of the diagnostic and prognostic effect of magnetic resonance imaging (MRI) based on multimodal feature fusion algorithm fo...