Other Cancers

A bibliometric analysis of research trends and future directions in early detection of pancreatic cancer.

BACKGROUND: Research on the early detection of pancreatic cancer has grown rapidly in recent years; however, existing bibliometric studies in this field have focused on broad research landscapes or treatment modalities, with no systematic analysis specifically mapping the knowledge structure and emerging frontiers of early detection. METHODS: Literature published between January 1, 1986, and Decem...

Mapping the research landscape of myelodysplastic syndromes: a scientometric analysis (2014-2025).

This scientometric study critically evaluates the global evolution of myelodysplastic syndromes (MDS) research from 2014 to 2025, aiming to integrate fragmented knowledge and identify emerging trends. A scientometric analysis was conducted using data retrieved from the Web of Science Core Collection on August 2, 2025. The search was restricted to "article" and "review" in English containing "Myelo...

Deep learning-driven MRI radiomics reveals biological subtypes and predicts recurrence risk in rectal cancer.

Traditional TNM staging inadequately captures the recurrence risk of rectal cancer (RC), limiting prognostic accuracy and personalized treatment decis...

Feasibility of deep learning-accelerated ultrafast T1-weighted VIBE Dixon imaging of the pelvis for screening of metastases in prostate MRI.

OBJECTIVE: This study aims to assess the image quality and perceived diagnostic confidence of research deep learning (DL)-accelerated T1-weighted "vol...

Oral squamous cell carcinoma diagnosis: an interpretable deep learning approach using multi-scale pathological images.

BACKGROUND: Diagnosis of oral squamous cell carcinoma (OSCC) currently relies heavily on the subjective experience of pathologists. This process is ti...

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), an...

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 iden...

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...

Integrative transcriptomic and CRISPR dependency analysis identifies hepatoblastoma-specific essential genes and actionable vulnerabilities.

BACKGROUND: Hepatoblastoma (HB) is the most common primary liver malignancy in childhood, yet its molecular determinants, functional dependencies, and...

Automated measurement of CD8+ T-cell distribution at the tumor epithelial-stromal interface is associated with NSCLC immunotherapy benefit and transcriptomic pathways.

Whereas anti-PD-(L)1 therapies are widely used in cancer treatment, only a subset of patients achieve long-term survival. Companion diagnostics based ...

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...