AIMC Topic: Carcinoma, Renal Cell

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Artificial Intelligence-Based Classification of Renal Oncocytic Neoplasms: Advancing From a 2-Class Model of Renal Oncocytoma and Low-Grade Oncocytic Tumor to a 3-Class Model Including Chromophobe Renal Cell Carcinoma.

Archives of pathology & laboratory medicine
CONTEXT.—: Distinguishing between renal oncocytic tumors, such as renal oncocytoma (RO), and a subset of tumors with overlapping characteristics, including the recently identified low-grade oncocytic tumor (LOT), can present a diagnostic challenge fo...

Tumor-Intrinsic and Microenvironmental Determinants of Impaired Antitumor Immunity in Chromophobe Renal Cell Carcinoma.

Journal of clinical oncology : official journal of the American Society of Clinical Oncology
PURPOSE: While immune checkpoint inhibition (ICI) has transformed the management of many advanced renal cell carcinomas (RCCs), the determinants of effective antitumor immunity for chromophobe RCC (ChRCC) and renal oncocytic tumors remain an unmet cl...

Discriminating Clear Cell From Non-Clear Cell Renal Cell Carcinoma: A Machine Learning Approach Using Contrast-enhanced Ultrasound Radiomics.

Ultrasound in medicine & biology
OBJECTIVE: The aim of this investigation is to assess the clinical usefulness of a machine learning model using contrast-enhanced ultrasound (CEUS) radiomics in discriminating clear cell renal cell carcinoma (ccRCC) from non-ccRCC.

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...

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 ...

[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...

Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.

Briefings in bioinformatics
Single-cell sequencing has advanced our understanding of cellular heterogeneity and disease pathology, offering insights into cellular behavior and immune mechanisms. However, extracting meaningful phenotype-related features is challenging due to noi...