AIMC Topic: Creatinine

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UroAngel: a single-kidney function prediction system based on computed tomography urography using deep learning.

World journal of urology
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 ...

Response accuracy of ChatGPT 3.5 Copilot and Gemini in interpreting biochemical laboratory data a pilot study.

Scientific reports
With the release of ChatGPT at the end of 2022, a new era of thinking and technology use has begun. Artificial intelligence models (AIs) like Gemini (Bard), Copilot (Bing), and ChatGPT-3.5 have the potential to impact every aspect of our lives, inclu...

The correlation between serum creatinine and burn severity and its predictive value.

Cellular and molecular biology (Noisy-le-Grand, France)
This study aimed to explore the correlation between serum creatinine and burn severity and the value of predicting the outcome of patients. For this purpose, a total of 268 burn patients (BUP) were collected. According to the burn area, they were div...

Handheld Biosensor System Based on a Gradient Grating Period Guided-Mode Resonance Device.

Biosensors
Handheld biosensors have attracted substantial attention for numerous applications, including disease diagnosis, drug dosage monitoring, and environmental sensing. This study presents a novel handheld biosensor based on a gradient grating period guid...

Examination of alternative eGFR definitions on the performance of deep learning models for detection of chronic kidney disease from fundus photographs.

PloS one
Deep learning (DL) models have shown promise in detecting chronic kidney disease (CKD) from fundus photographs. However, previous studies have utilized a serum creatinine-only estimated glomerular rate (eGFR) equation to measure kidney function despi...

Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine.

Kidney360
KEY POINTS: The authors leverage the unique benefits of panoptic segmentation to perform the largest ever quantitation of reference kidney morphometry. Kidney features vary with age and sex; and glomeruli size may intricately link to creatinine, defy...

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

Cancer medicine
BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of toxicity and should therefore be monitored. We aimed to develop a machine learning model to identify those patients that need closer monitoring, enabl...

Prediction of Postoperative Creatinine Levels by Artificial Intelligence after Partial Nephrectomy.

Medicina (Kaunas, Lithuania)
: Multiple factors are associated with postoperative functional outcomes, such as acute kidney injury (AKI), following partial nephrectomy (PN). The pre-, peri-, and postoperative factors are heavily intertwined and change dynamically, making it diff...

Minimally invasive nephron-sparing treatments for T1 renal cell cancer in patients over 75 years: a comparison of outcomes after robot-assisted partial nephrectomy and percutaneous ablation.

European radiology
PURPOSE: To compare the oncological and perioperative outcomes of robot-assisted partial nephrectomy (RPN) and percutaneous thermal ablation (PTA) for treatment of T1 renal cell cancer (RCC) in patients older than 75 years.

Deep Learning Identifies Intelligible Predictors of Poor Prognosis in Chronic Kidney Disease.

IEEE journal of biomedical and health informatics
Early diagnosis and prediction of chronic kidney disease (CKD) progress within a given duration are critical to ensure personalized treatment, which could improve patients' quality of life and prolong survival time. In this study, we explore the inte...