AIMC Topic: Nephrectomy
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Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.
Scientific reports
Jul 1, 2025
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...
Surgeons versus computer vision: a comparative analysis on surgical phase recognition capabilities.
International journal of computer assisted radiology and surgery
May 31, 2025
PURPOSE: Automated surgical phase recognition (SPR) uses artificial intelligence (AI) to segment the surgical workflow into its key events, functioning as a building block for efficient video review, surgical education as well as skill assessment. Pr...
Artificial Intelligence Based Augmented Reality Navigation in Minimally Invasive Partial Nephrectomy.
Urology
Feb 25, 2025
OBJECTIVE: To explore the role of artificial intelligence based augmented reality intraoperative real-time navigation in minimally invasive partial nephrectomy to standardize renal hilum dissection procedures and improve operative efficiency.
A Fully Automated Artificial Intelligence-Based Approach to Predict Renal Function After Radical or Partial Nephrectomy.
Urology
Feb 4, 2025
OBJECTIVE: To test if our artificial intelligence (AI)-postoperative glomerular filtration rate (GFR) prediction is as accurate as a validated clinical model. The American Urologic Association recommends estimating postoperative GFR in patients with ...
Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy.
BMC nephrology
Dec 18, 2024
BACKGROUND: Chronic Kidney Disease (CKD) is a common severe complication after radical nephrectomy in patients with renal cancer. The timely and accurate prediction of the long-term progression of renal function post-surgery is crucial for early inte...
Impact of different nephrectomy types on M0 renal cell carcinoma outcomes in a propensity score matching and deep learning study.
Scientific reports
Nov 11, 2024
There are few analyses comparing complete nephrectomy with resection of the renal parenchyma only (CN) or radical nephrectomy that includes simultaneous resection of the parenchyma, affected perirenal fascia, perirenal fat, and ureter (RN) relative t...
A machine learning-based analysis for the definition of an optimal renal biopsy for kidney cancer.
Urologic oncology
Nov 7, 2024
OBJECTIVE: Renal Tumor biopsy (RTB) can assist clinicians in determining the most suitable approach for treatment of renal cancer. However, RTB's limitations in accurately determining histology and grading have hindered its broader adoption and data ...
The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study.
International journal of surgery (London, England)
Nov 1, 2024
BACKGROUND: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed t...
Personalized Prediction of Long-Term Renal Function Prognosis Following Nephrectomy Using Interpretable Machine Learning Algorithms: Case-Control Study.
JMIR medical informatics
Sep 20, 2024
BACKGROUND: Acute kidney injury (AKI) is a common adverse outcome following nephrectomy. The progression from AKI to acute kidney disease (AKD) and subsequently to chronic kidney disease (CKD) remains a concern; yet, the predictive mechanisms for the...
Prediction of post-donation renal function using machine learning techniques and conventional regression models in living kidney donors.
Journal of nephrology
Jul 29, 2024
BACKGROUND: Accurate prediction of renal function following kidney donation and careful selection of living donors are essential for living-kidney donation programs. We aimed to develop a prediction model for post-donation renal function following li...
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