AIMC Topic: Urinary Bladder Neoplasms

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Microbial Product Cocktails for Personalized Cancer Immunotherapy.

Nature communications
The human immune system has evolved to interact with various commensal and pathogenic bacteria in intricate and nuanced ways. While the diversity of bacteria presents fundamental challenges in understanding immune-microbe interactions, it also offers...

Explainable and likelihood aware AI framework for MRI-based pixel-level bladder tumour prediction.

Scientific reports
Bladder tumours (BTs) pose significant clinical challenges due to their high recurrence rates and risk of progression to invasive malignancies, which emphasises the need for early and accurate detection. Magnetic resonance imaging (MRI), with its sup...

Comprehensive analysis of coagulation-associated gene signature in bladder cancer diagnosis, prognosis, and immunotherapy.

Scientific reports
In recent years, research on the relationship between coagulation system abnormalities and tumor immunity has been widely reported. Bladder cancer (BC), as an immunogenic tumor, holds great promise in immunotherapy. The role of coagulation-related ge...

Multi-institutional validation of AI models for classifying urothelial neoplasms in digital pathology.

Scientific reports
This study proposes a deep learning approach for classifying normal, noninvasive, and invasive urothelial neoplasms via digitized histopathologicalimages. Despite many artificial intelligence (AI) models for cancer diagnosis, few focus on bladder les...

Evaluation of inflammatory markers in survival analysis of patients undergoing radical cystectomy using machine learning.

World journal of urology
BACKGROUND: We aimed to create a Machine learning (ML) model using patient demographic, clinical and pathological data for prediction of overall survival in patients treated with radical cystectomy (RC). Secondly, we evaluated whether inflammatory ma...

CCDC137 knockdown suppresses bladder cancer progression by downregulating SCD.

Journal of translational medicine
BACKGROUND: The Coiled-coil domain-containing (CCDC) family, due to its unique protein structural domain and broad involvement in diverse biological processes, has emerged as a focus in oncology research. Nevertheless, its clinical significance and f...

Deep learning-based spatial analysis on tumor and immune cells of pathology images predicts MIBC prognosis.

PloS one
OBJECTIVE: Muscle-invasive bladder cancer (MIBC) is a highly aggressive disease with a poor prognosis. This study aims to explore the correlation between the spatial distribution of lymphocyte aggregates and the prognosis of MIBC using deep learning.

Graph theoretic and machine learning approaches in molecular property prediction of bladder cancer therapeutics.

Scientific reports
This work introduces a hybrid computational approach in which degree-based topological descriptors are harnessed with the aid of advanced regression models and artificial neural networks (ANNs) to predict the crucial physicochemical properties of 17 ...

Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.

Scientific reports
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an...

Identification and single-cell analysis of prognostic genes related to mitochondrial and neutrophil extracellular traps in bladder cancer.

Scientific reports
The development of bladder cancer (BLCA) is associated with mitochondrial dysfunction and neutrophil extracellular traps (NETs); however, the relationship between mitochondrial function and NET formation in BLCA remains poorly understood. In this stu...