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Ischemia

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Influences of Edaravone on Necroptosis-Related Proteins and Oxidative Stress in Rats with Lower Extremity Ischemia/Reperfusion Injury.

Cellular and molecular biology (Noisy-le-Grand, France)
The study aimed to investigate the influences of edaravone on necroptosis-related proteins and oxidative stress in rats with lower extremity ischemia/reperfusion (I/R) injury. The normal group (n=10), model group (lower extremity I/R injury model, n=...

Development of a Fuzzy Diagnostic Model of Ischemic Disease of the Lower Limbs for Different Stages of Patient Management.

Critical reviews in biomedical engineering
Ischemic disease has severe impact on patients which makes accurate diagnosis vital for health protection. Improving the quality of prediction of patients with ischemic extremity disease by using hybrid fuzzy model allows for early and accurate progn...

Deep-learning-based AI for evaluating estimated nonperfusion areas requiring further examination in ultra-widefield fundus images.

Scientific reports
We herein propose a PraNet-based deep-learning model for estimating the size of non-perfusion area (NPA) in pseudo-color fundus photos from an ultra-wide-field (UWF) image. We trained the model with focal loss and weighted binary cross-entropy loss t...

Accurate intraoperative real-time blood flow assessment of the remnant stomach during robot-assisted distal pancreatectomy with celiac axis resection using indocyanine green fluorescence imaging and da Vinci Firefly technology.

Asian journal of endoscopic surgery
INTRODUCTION: Ischemic gastropathy is one of the unique postoperative complications associated with distal pancreatectomy with celiac axis resection for locally advanced pancreatic cancer. Therefore, it is essential to evaluate blood flow to the stom...

A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.

Computers in biology and medicine
Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the...

Open versus robot-assisted partial nephrectomy for highly complex renal masses: a meta-analysis of perioperitive and functional outcomes.

Journal of robotic surgery
Robot-assisted partial nephrectomy (RAPN) is increasingly being used for the complex surgical management of renal masses. The comparison of RAPN with open partial nephrectomy (OPN) has not yet led to a unified conclusion with regard to perioperative ...

The Association of Ischemia Type and Duration with Acute Kidney Injury after Robot-Assisted Partial Nephrectomy.

Current oncology (Toronto, Ont.)
BACKGROUND: Acute kidney injury (AKI) after robot-assisted partial nephrectomy (RAPN) is a robust surrogate for chronic kidney disease. The objective of this study was to evaluate the association of ischemia type and duration during RAPN with postope...

Machine and deep learning models for accurate detection of ischemia and scar with myocardial blood flow positron emission tomography imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: Quantification of myocardial blood flow (MBF) is used for the noninvasive diagnosis of patients with coronary artery disease (CAD). This study compared traditional statistics, machine learning, and deep learning techniques in their abilit...

Single-Port Multiport Robot-Assisted Partial Nephrectomy: A Meta-Analysis.

Journal of endourology
Several centers have reported their experience with single-port robot-assisted partial nephrectomy (SP-RAPN); however, it is uncertain if utilization of this platform represents an improvement in outcomes compared to multiport robot-assisted partial...

Bibliometric Analysis of Machine Learning Applications in Ischemia Research.

Current problems in cardiology
OBJECTIVE: The objective of this study is to conduct a comprehensive bibliometric analysis to elucidate the landscape of machine learning applications in ischemia research.