AIMC Topic: Kidney Neoplasms
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Differentiating between renal medullary and clear cell renal carcinoma with a machine learning radiomics approach.
The oncologist
Feb 6, 2025
BACKGROUND: The objective of this study was to develop and validate a radiomics-based machine learning (ML) model to differentiate between renal medullary carcinoma (RMC) and clear cell renal carcinoma (ccRCC).
Preoperative kidney tumor risk estimation with AI: From logistic regression to transformer.
PloS one
Jan 1, 2025
We consider the problem of renal mass risk classification to support doctors in adjuvant treatment decisions following nephrectomy. Recommendation of adjuvant therapy based on the mass appearance poses two major challenges: first, morphologic pattern...
Autoencoder techniques for survival analysis on renal cell carcinoma.
PloS one
Jan 1, 2025
Survival is the gold standard in oncology when determining the real impact of therapies in patients outcome. Thus, identifying molecular predictors of survival (like genetic alterations or transcriptomic patterns of gene expression) is one of the mos...
Artificial intelligence can help individualize Wilms tumor treatment by predicting tumor response to preoperative chemotherapy.
Investigative and clinical urology
Jan 1, 2025
PURPOSE: To create a computer-aided prediction (CAP) system to predict Wilms tumor (WT) responsiveness to preoperative chemotherapy (PC) using pre-therapy contrast-enhanced computed tomography (CECT).
Vincristine
Wilms Tumor
Dactinomycin
Kidney Neoplasms
Nephrectomy
Preoperative Care
Female
Male
Infant
Adolescent
Child, Preschool
Child
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Artificial Intelligence
Precision Medicine
Retrospective Studies
Tomography, X-Ray Computed
Humans
Survival analysis of clear cell renal cell carcinoma based on radiomics and deep learning features from CT images.
Medicine
Dec 20, 2024
PURPOSE: To create a nomogram for accurate prognosis of patients with clear cell renal cell carcinoma (ccRCC) based on computed tomography images.
[Application and research progress of artificial intelligence in pathological diagnosis of renal cell carcinoma].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Aug 8, 2024
Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self-supervised deep learning.
Cancer medicine
Aug 1, 2024
BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC), such as guiding adjuvant chemotherapy and improving clinical outcomes. However, the time-consumin...
Selective Clamping for Robot-Assisted Surgical Procedures.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Partial nephrectomy, the gold standard treatment for renal tumors, is performed with clamping of the renal arteries, in order to interrupt the blood flowing towards the tumor. However, the temporary interruption of arterial flow may lead to ischemia ...
Deciphering the tumour microenvironment of clear cell renal cell carcinoma: Prognostic insights from programmed death genes using machine learning.
Journal of cellular and molecular medicine
Jul 1, 2024
Clear cell renal cell carcinoma (ccRCC), a prevalent kidney cancer form characterised by its invasiveness and heterogeneity, presents challenges in late-stage prognosis and treatment outcomes. Programmed cell death mechanisms, crucial in eliminating ...
The expanding role of artificial intelligence in the histopathological diagnosis in urological oncology: a literature review.
Folia medica
Jun 30, 2024
The ongoing growth of artificial intelligence (AI) involves virtually every aspect of oncologic care in medicine. Although AI is in its infancy, it has shown great promise in the diagnosis of oncologic urological conditions. This paper aims to explor...
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