Other Cancers

Multimodal deep learning-based prediction of radiation-induced temporal lobe injury via anatomical imaging and spatial dose: A multicenter study.

BACKGROUND: To develop and validate a multimodal deep learning model for pre-treatment prediction of radiation-induced temporal lobe injury (RTLI), and to evaluate its generalizability across nasopharyngeal carcinoma-endemic and non-endemic regions. METHODS: In this multicenter retrospective study, 6847 patients with nasopharyngeal carcinoma from five institutions in southern and northern China we...

A fatty acid metabolism-based deep learning model predicts biochemical recurrence and identifies NUDT19 as a candidate metabolic factor in prostate cancer.

PURPOSE: To develop a fatty acid metabolism-based deep learning model for predicting biochemical recurrence (BCR) in prostate cancer (PCa) and to identify recurrence-associated metabolic regulators. METHODS: Transcriptomic data from TCGA and GEO GSE70769 were integrated to identify fatty acid metabolism-related genes and construct a deep learning model for BCR prediction. Tumor-infiltrating lympho...

Identification of T-cell exhaustion-related biomarkers in aortic dissection via integrated multi-omics analysis and mendelian randomization.

BACKGROUND: Aortic dissection (AD) is a life-threatening cardiovascular emergency characterized by high acute mortality. While immune dysregulation is...

A perioperative multi-modal fusion and deep learning-based prognostic system for upper tract urothelial carcinoma: a multi-institutional study.

OBJECTIVES: Precise perioperative risk stratification for upper tract urothelial carcinoma (UTUC) is essential. We developed a multimodal prognostic m...

Machine learning-powered audio-omics processing method as an auxiliary diagnostic approach for advanced nasopharyngeal carcinoma.

PURPOSE: Nasopharyngeal carcinoma (NPC) is located in the nasopharyngeal mucosa and is a malignant tumour of the head and neck, and approximately 70% ...

ACOT9, a mitochondrial metabolism-related gene, promotes ROS-associated epithelial remodeling in laryngeal squamous cell carcinoma.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is characterized by mitochondrial metabolic reprogramming, but its prognostic significance and un...

Early risk prediction in endometrial cancer using biomarker and machine learning models: a systematic review and meta-analysis protocol.

BACKGROUND: Globally, endometrial cancer (EC) is among the most prevalent gynaecological cancers, with rising incidence driven by demographic and meta...

Benchmarking of AI and Radiologists for Indeterminate Lung Nodule Malignancy Risk Estimation on Screening CT: The LUNA25 Challenge.

Purpose To compare the performance of an artificial intelligence (AI) system with that of radiologists for estimating malignancy risk of indeterminate...

Cancer-Associated Alterations In O-GalNAc Glycosylation.

Aberrant O-GalNAc glycans such as Tn, STn, and T are among the most consistent tumor-associated carbohydrate antigens, broadly expressed on carcinomas...

Prevalence aware feature selection improves biomarker identification in microbiome studies.

MOTIVATION: Identifying robust microbial biomarkers is crucial for disease diagnosis and prediction, elucidation of biological mechanisms, and develop...

Advances in the management of pediatric low-grade glioma.

Pediatric low-grade gliomas (pLGGs), the most common CNS tumors in children, are increasingly recognized as chronic diseases with prolonged courses an...

Artificial intelligence in endoscopic prediction of submucosal invasion in gastric neoplasms: systematic review and meta-analysis.

BACKGROUND: Accurate assessment of Submucosal (SM) invasion in gastric neoplasms is vital for curative endoscopic management, yet conventional endosco...

Annexin A2 as a Therapeutic Target of Artemisiae Scopariae Herba-derived Quercetin in Preventing Malignant Progression from Primary Sclerosing Cholangitis to Cholangiocarcinoma: An Integrative Study.

ETHNOPHARMACOLOGICAL RELEVANCE: Artemisiae Scopariae Herba (ASH) is traditionally used to treat cholestatic liver diseases and exhibits anti-tumour po...

Molecular characteristics and modifications of glioblastoma affecting the efficacy of immunotherapy.

Glioblastoma is a highly aggressive brain tumor characterized by complex genetic, molecular, and epigenetic features that present significant challeng...

Artificial intelligence-guided analysis of the tumor microenvironment predicts response to pembrolizumab in rare tumors.

BACKGROUND: Pathologic tumor response and changes in the tumor microenvironment (TME) predict outcomes to immune checkpoint inhibitors, but are unders...

Efficacy and safety of multiple treatments for small hepatocellular carcinoma: an updated systematic review and component network meta analysis.

BACKGROUND: This is an updated component network meta-analysis to evaluate efficacy and safety of various therapeutic approaches and their combination...

Using machine learning algorithms based on laboratory indicators to establish a diagnostic model for lung cancer.

BACKGROUND: Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Current diagnostic strategies rely primarily on imagi...

Single-model deep learning approach for simultaneous cervical vertebral maturation staging and skeletal jaw relationship on lateral cephalograms using YOLOv8 and CNN.

BACKGROUND: This study aimed to develop an integrated artificial intelligence (AI) pipeline for cervical vertebral maturation (CVM) staging and skelet...

Multi-omics integration and clinical validation identify CKAP2 as a diagnostic biomarker for bladder cancer.

BACKGROUND: Bladder cancer (BC) remains a prevalent malignancy with a high recurrence rate; however, the lack of specific biomarkers hinders early det...

Genetically engineered outer membrane vesicles as next-generation bionanomaterials for therapeutic and diagnostic applications.

Outer membrane vesicles (OMVs), naturally released by Gram-negative bacteria, represent a unique class of bionanomaterials with inherent immunogenicit...