Other Cancers

and are potentially important biomarkers for early diagnosis and treatment of esophageal squamous cell carcinoma: based on WGCNA and machine learning analysis.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) does not have distinct and highly sensitive bi...

Impact of ITH on PRAD patients and feasibility analysis of the positive correlation gene MYLK2 applied to PRAD treatment.

INTRODUCTION: Prostate adenocarcinoma (PRAD) is an extremely widespread site of urological malignanc...

Transformer model based on Sonazoid contrast-enhanced ultrasound for microvascular invasion prediction in hepatocellular carcinoma.

BACKGROUND: Microvascular invasion (MVI) is strongly associated with the prognosis of patients with ...

Integrative analysis of epigenetic and transcriptional interrelations identifies histotype-specific biomarkers in early-stage ovarian carcinoma.

BACKGROUND: Epithelial ovarian cancer (EOC) is a deadly and heterogenous disease comprising five maj...

The Role of Machine Learning to Detect Occult Neck Lymph Node Metastases in Early-Stage (T1-T2/N0) Oral Cavity Carcinomas.

OBJECTIVE: Oral cavity carcinomas (OCCs) represent roughly 50% of all head and neck cancers. The ris...

Data-Driven Defragmentation: Achieving Value-Based Sarcoma and Rare Cancer Care Through Integrated Care Pathway Mapping.

Sarcomas, a rare and complex group of cancers, require multidisciplinary care across multiple health...

Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images.

OBJECTIVES: Lymphovascular invasion significantly impacts the prognosis of urothelial carcinoma of t...

Machine Learning-based Dose Prediction in [Lu]Lu-PSMA-617 Therapy by Integrating Biomarkers and Radiomic Features from [Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography.

PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorb...

The Role of Artificial Intelligence (ChatGPT-4o) in Supporting Tumor Board Decisions.

Artificial intelligence (AI) has emerged as a promising field in the era of personalized oncology d...

Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends.

The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major ...

MRI-based radiomics for differentiating high-grade from low-grade clear cell renal cell carcinoma: a systematic review and meta-analysis.

PURPOSE: High-grade clear cell renal cell carcinoma (ccRCC) is linked to lower survival rates and mo...

Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva.

: Despite great efforts from both clinical and pathological sides to address the extent of metastati...

Radiomics of Dynamic Contrast-Enhanced MRI for Predicting Radiation-Induced Hepatic Toxicity After Intensity Modulated Radiotherapy for Hepatocellular Carcinoma: A Machine Learning Predictive Model Based on the SHAP Methodology.

OBJECTIVE: To develop an interpretable machine learning (ML) model using dynamic contrast-enhanced m...

Fibrogenesis-driven tumor progression in clear cell renal cell carcinoma: prognostic, therapeutic implications and the dual role of neuropilin-1.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal cancer, with...

Artificial intelligence-assisted CT radiomics: redefining preoperative prediction of lateral cervical lymph node metastasis in papillary thyroid carcinoma.

MRI Radiomics to Predict Early Treatment Response to TACE Combined with Lenvatinib Plus a PD-1 Inhibitor for Hepatocellular Carcinoma with Portal Vein Tumor Thrombus.

PURPOSE: To develop and validate a predictor for early treatment response in hepatocellular carcinom...

Comparison of Manual Versus QuPath Software-based Immunohistochemical Scoring Using Oral Squamous Cell Carcinoma as a Model.

Gold standard for immunohistochemical analyses is the manual assessment by two specialist pathologis...

Predicting Immunotherapy Response in Unresectable Hepatocellular Carcinoma: A Comparative Study of Large Language Models and Human Experts.

Hepatocellular carcinoma (HCC) is an aggressive cancer with limited biomarkers for predicting immuno...

Tumor budding and poorly differentiated clusters as a biological continuum in colorectal cancer invasion and prognosis.

Tumor budding (TB) and poorly differentiated clusters (PDCs) are features of infiltrative growth pat...

Deciphering Shared Gene Signatures and Immune Infiltration Characteristics Between Gestational Diabetes Mellitus and Preeclampsia by Integrated Bioinformatics Analysis and Machine Learning.

Gestational diabetes mellitus (GDM) and preeclampsia (PE) are common and serious disorders of pregna...

A novel model for predicting immunotherapy response and prognosis in NSCLC patients.

BACKGROUND: How to screen beneficiary populations has always been a clinical challenge in the treatm...