Other Cancers

Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor in women globally, with tobacco smoke being a major environmental risk factor. The tobacco-specific metabolite cotinine may promote cancer progression through mechanisms such as chronic inflammation and genomic instability, but its precise molecular targets and interactions remain unclear. METHODS: We integrated network toxicolo...

Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Some researchers have explored the application of radiomics-based machine learning to detect preoperative muscle invasion, high-grade tumors, human epidermal growth factor receptor 2 expression, and other risk factors for bladder cancer. However, systematic evidence proving its effectiveness remains lacking. OBJECTIVE: This study aimed to evaluate the performance of radiomics-based mac...

Toward generalizable prediction of cancer signal using a cell-free DNA language model.

Cell-free DNA can be used for early cancer detection, minimal residual disease monitoring, and post-treatment risk stratification. However, current as...

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lu...

New Frontiers of Skin Ultrasound in Precision Medicine.

Ultrasound has emerged as a versatile, non-invasive imaging technique in dermatology, offering real-time, high-resolution visualization of cutaneous s...

A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.

Malignant intestinal obstruction (MIO) is a severe complication of advanced cancer. Traditional static assessment models struggle to capture its dynam...

Performance of GPT-based large language models in hepatocellular carcinoma stratification: liver function assessment, BCLC staging, and treatment recommendations.

Large language models (LLMs) like GPT have been proposed to support complex clinical decision-making. This study evaluated the performance of GPT-base...

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.

Acute myeloid leukemia (AML) is a genetically and phenotypically heterogeneous hematological malignancy. Here, to better define this clinically taxing...

Interpretable machine learning distinguishes skip from continuous metastasis in N1b papillary thyroid carcinoma.

Skip metastasis-defined as lateral lymph node metastasis(N1b) in the absence of central lymph node involvement-represents a distinct yet underrecogniz...

Innovative strategies to overcome cancer drug resistance: from nanodelivery systems to targeted therapeutics.

Cancer drug resistance, driven by complex genetic mutations, epigenetic plasticity, and tumor microenvironment interactions, remains the primary cause...

Side-level versus patient-level evaluation in four-view mammography classification: a comprehensive benchmark on the CMMD dataset.

BACKGROUND: Deep learning for mammographic image classification yields impressive performance metrics, but inconsistent evaluation methodologies-speci...

Fusion of MRI-radiomics and clinical features to improve pathological T-stage prediction of rectal cancer: a multicenter study.

BACKGROUND: Developing a rational model for precise preoperative staging of rectal cancer using magnetic resonance imaging is crucial for improving th...

Deep learning-based prediction of gene expression from histopathology identifies NR5A1 as a candidate biomarker and druggable target in high-grade serous ovarian carcinoma.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) is the most lethal ovarian cancer subtype, responsible for ~ 70% of ovarian cancer-related deaths...

Wavelet Spectrum in a Multi-Channel Network May Reduce Biopsy Rates on Diagnosis of Breast Tumors with BI-RADS Category 4a or Higher.

OBJECTIVES: BI-RADS 4a+ breast tumors have a high rate of unnecessary biopsies due to ambiguous diagnostic features. This study aims to develop and ev...

A Single-Cell Guided Machine Learning Model Predicts Response to Immune Checkpoint Inhibitors in Gastric Cancer.

Resistance to immune checkpoint inhibitors is a major clinical obstacle in the treatment of gastric cancer. Identifying drug-resistant cell population...

Functional Imaging in Hereditary Endocrine Neoplasms: Evolving Modalities and Clinical Implications.

Hereditary endocrine neoplastic syndromes require structured, lifelong surveillance owing to their multisystem involvement, variable penetrance, and h...

Deep learning applications in cancer treatment Prediction: Comprehensive research foundation for systematic review and Meta-Analysis.

Deep learning has rapidly emerged as a transformative technology in oncology, offering new capabilities in treatment response prediction and personali...

Machine Learning-Driven Prognostic Modeling in Head and Neck Adenoid Cystic Carcinoma: A Retrospective Cohort Study.

INTRODUCTION: Adenoid cystic carcinoma (ACC) of the head and neck is a rare malignancy characterized by perineural invasion, local recurrence, and dis...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Label-free classification of breast cancer subtypes in ex vivo human tissues using Raman spectroscopy and machine learning.

Breast conserving surgery (BCS) aims to excise breast tumors whilst preserving breast-related quality of life, but is complicated by the challenge of ...