AIMC Topic: Kidney Neoplasms

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Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.

Radiology. Imaging cancer
Purpose To assess the agreement between routine-dose (RD) and lower-dose (LD) contrast-enhanced CT scans, with and without Digital Imaging and Communications in Medicine-based deep learning-based denoising (DLD), in evaluating small renal masses (SRM...

Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSES: This study aimed to develop a computed tomography (CT)-based multi-organ segmentation model for delineating organs-at-risk (OARs) in pediatric upper abdominal tumors and evaluate its robustness across multiple datasets.

A Spatial Metabolomics Annotation Workflow Leveraging Cyclic Ion Mobility and Machine Learning-Predicted Collision Cross Sections.

Journal of the American Society for Mass Spectrometry
In nontargeted spatial metabolomics, accurate annotation is crucial for understanding metabolites' biological roles and spatial patterns. MS mass spectrometry imaging (MSI) coverage is often incomplete or nonexistent, resulting in many unknown featur...

From planning to prognosis: predicting renal function after minimally-invasive partial nephrectomy with artificial intelligence.

Minerva urology and nephrology
This study presents a machine learning model to predict renal function decline following minimally-invasive partial nephrectomy. Using a dataset of 556 patients treated between 2015 and 2023, the model incorporated patient, tumor, and intraoperative ...

Integrated machine learning survival framework develops a prognostic model based on macrophage-related genes and programmed cell death signatures in a multi-sample Kidney renal clear cell carcinoma.

Cell biology and toxicology
BACKGROUND: Macrophages are closely associated with the progression of Kidney renal clear cell carcinoma (KIRC) and can influence programmed cell death (PCD) of tumour cells. To identify prognostic biomarkers for KIRC, it is essential to investigate ...

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Scientific reports
Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration, exhibits limited sensitivity to conventional radiochemotherapy. Although immunotherapy has shown efficacy in some patients, its applicability is not ...

Application of BOLDMRIbased radiomics in differentiating malignant from benign renal tumors.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: Blood oxygen level dependent magnetic resonance imaging (BOLD-MRI) is a kind of non-invasive MRI technology which reflects the tissue blood oxyen levels. This stuy aims to explore the value of radiomics based on BOLD-MRI in differentiatin...

[ARTIFICIAL INTELLIGENCE-ASSISTED LITERATURE REVIEW: A CASE STUDY IN FUMARATE HYDRATASE-DEFICIENT RENAL CELL CARCINOMA].

Harefuah
Fumarate hydratase-deficient renal cell carcinoma (FHdRCC) is a rare and aggressive form of kidney cancer that presents significant therapeutic challenges. Due to its rarity, treatment decisions often rely on comprehensive literature reviews to ident...