AIMC Topic: Kidney
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Automated Analysis of Split Kidney Function from CT Scans Using Deep Learning and Delta Radiomics.
Journal of endourology
May 16, 2024
Differential kidney function assessment is an important part of preoperative evaluation of various urological interventions. It is obtained through dedicated nuclear medical imaging and is not yet implemented through conventional Imaging. We assess...
Development and External Validation of a Multidimensional Deep Learning Model to Dynamically Predict Kidney Outcomes in IgA Nephropathy.
Clinical journal of the American Society of Nephrology : CJASN
May 10, 2024
KEY POINTS: A dynamic model predicts IgA nephropathy prognosis based on deep learning. Longitudinal clinical data and deep learning improve predictive accuracy and interpretability in GN.
Vision-based estimation of manipulation forces by deep learning of laparoscopic surgical images obtained in a porcine excised kidney experiment.
Scientific reports
Apr 27, 2024
In robot-assisted surgery, in which haptics should be absent, surgeons experience haptics-like sensations as "pseudo-haptic feedback". As surgeons who routinely perform robot-assisted laparoscopic surgery, we wondered if we could make these "pseudo-h...
Predicting the presence of adherent perinephric fat using MRI radiomics combined with machine learning.
International journal of medical informatics
Apr 26, 2024
OBJECTIVES: Adherent perinephric fat (APF) poses significant challenges to surgical procedures. This study aimed to evaluate the usefulness of machine learning algorithms combined with MRI-based radiomics features for predicting the presence of APF.
Predicting osteoporosis from kidney-ureter-bladder radiographs utilizing deep convolutional neural networks.
Bone
Apr 25, 2024
Osteoporosis is a common condition that can lead to fractures, mobility issues, and death. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for osteoporosis, it is expensive and not widely available. In contrast, kidney-ureter-bla...
Deep-learning model for evaluating histopathology of acute renal tubular injury.
Scientific reports
Apr 19, 2024
Tubular injury is the most common cause of acute kidney injury. Histopathological diagnosis may help distinguish between the different types of acute kidney injury and aid in treatment. To date, a limited number of study has used deep-learning models...
Reproducibility and prognostic ability of chronicity parameters in kidney biopsy - Comprehensive evaluation comparing microscopy and artificial intelligence in digital pathology.
Human pathology
Apr 18, 2024
INTRODUCTION: Semi-quantitative scoring of various parameters in renal biopsy is accepted as an important tool to assess disease activity and prognostication. There are concerns on the impact of interobserver variability in its prognostic utility, ge...
Polyomavirus Infections
Microscopy
Image Interpretation, Computer-Assisted
Observer Variation
Artificial Intelligence
Algorithms
Humans
Middle Aged
Kidney
Glomerular Filtration Rate
Biopsy
Fibrosis
Kidney Diseases
Predictive Value of Tests
Reproducibility of Results
Aged
Adult
Male
Kidney Transplantation
Prognosis
Female
UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.
World journal of urology
Apr 16, 2024
BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) is clinically crucial for determining the status of obstruction, developing treatment strategies, and predicting prognosis in obstructive nephropathy (ON). We aimed to develop a ...
Assessing the perioperative outcomes of abdominal drain omission after robot-assisted partial nephrectomy.
Scientific reports
Apr 15, 2024
The study aimed to evaluate the impact of abdominal drain placement (vs. omission) on perioperative outcomes of robot-assisted partial nephrectomy (RAPN), focusing on complications, time to canalization, deambulation, and pain management. A prospecti...
[Artificial intelligence in kidney transplant pathology].
Pathologie (Heidelberg, Germany)
Apr 10, 2024
BACKGROUND: Artificial intelligence (AI) systems have showed promising results in digital pathology, including digital nephropathology and specifically also kidney transplant pathology.
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