Other Cancers

A Thyroid Nodule Differentiation Model for Benign-Malignant Identification by Fusing Transfer Learning and Gradient Boosting Decision Tree.

Accurate identification of benign and malignant thyroid nodules is a core link in clinical diagnosis and treatment decision-making, which directly affects the selection of subsequent treatment plans for patients. Aiming at the problems such as the strong subjectivity of traditional ultrasound diagnosis and the insufficient generalization ability of a single artificial intelligence model in small-s...

Assessing the proinflammatory potential of sterile fecal microbiome filtrate from ulcerative colitis patients using an intestine-on-chip platform and automated image analysis.

BACKGROUND AND AIMS: Ulcerative colitis (UC) is characterized by disruptions of the gut microbiome and an exaggerated mucosal immune response in genetically susceptible individuals. Alterations in the composition of the intestinal metabolome associated with dysbiosis can trigger chronic inflammation. However, it remains unclear whether microbial dysbiosis is the cause or consequence of chronic muc...

Artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis of the landscape.

This bibliometric analysis examines the transformative role of artificial intelligence (AI) in immune checkpoint inhibitor (ICI) research. Using VOSvi...

The Performance of ChatGPT-4o and DeepSeek-R1 in Interpreting Thyroid Nodule Ultrasound Text Reports: Multicenter Study.

BACKGROUND: Although thyroid nodules are detected in up to 60% of adults on ultrasound, the vast majority are benign, creating a substantial decision-...

Haematological pre-staging of colorectal cancer: Longitudinal trends identify high-risk metastatic phenotypes 24 months prior to diagnosis.

BACKGROUND: The latent systemic phase of colorectal cancer (CRC) offers a critical but often missed window for early intervention. This study evaluate...

Integrating single-cell and bulk transcriptomics to identify a SUMOylation-related prognostic signature and the oncogenic role of VPS72 in hepatocellular carcinoma.

INTRODUCTION: Hepatocellular carcinoma (HCC) is a highly aggressive malignancy characterized by limited therapeutic options and significant cellular h...

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers...

Fusion Gene Detection Enhances Clinical Outcome Prediction of Hepatocellular Carcinoma Through Machine Learning Analyses.

Hepatocellular carcinoma is one of the most lethal malignancies for humans. Assessing the clinical outcomes of HCC remains challenging. In this study,...

Classification of malignant/benign groups in lung cancer by machine learning and investigation of feature significance of parameters.

OBJECTIVES: This study aimed to apply machine learning (ML) models to enhance lung cancer (LC) classification, distinguishing malignant from benign tu...

Combined Analysis of scRNA-seq and Bulk RNA-seq Sequencing Revealing the Heterogeneity of Recurrent Respiratory Papillomatosis and Key Molecular Mechanisms of Its Occurrence and Development.

OBJECTIVE: Recurrent respiratory papillomatosis (RRP) is a benign tumor that is highly prone to recurrence and has the potential to become malignant, ...

Single-cell and spatial transcriptomic landscapes reveal PIGT as a pivotal regulator of immunometabolic remodeling in colorectal cancer liver metastasis.

Colorectal cancer liver metastasis (CRLM) represents the leading cause of mortality in colorectal cancer (CRC). However, the molecular mechanisms enab...

Cross-modal mapping of cancer stem-like cell plasticity using deep learning.

Cancer stem-like cells (CSCs) play a pivotal role in driving tumor heterogeneity, therapeutic resistance, and disease progression. Despite the power o...

Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review.

BACKGROUND AND AIMS: Solid tumors emerge from uncontrolled cell division and interactions with neighboring cells that influence their growth and resis...

Cross-species ALP-associated gene signature from canine osteosarcoma stratifies metastatic status in human osteosarcoma: A comparative oncology approach.

Osteosarcoma (OSA) is an aggressive primary bone tumor of humans and dogs, with metastatic progression remaining the major determinant of poor outcome...

Targeted radionuclide-drug conjugates: Current status and perspectives.

Radionuclide drug conjugates (RDCs) are emerging molecular platforms for diagnostic imaging, targeted radionuclide therapy, and precision-oncology the...

Diagnostic performance of ¹⁸F-FDG PET/CT radiomics-based machine learning models for pancreatic lesion characterisation: Comparison with visual assessment and evaluation of human-radiomics synergy.

PURPOSE: We aimed to evaluate the diagnostic performance of ¹⁸F-FDG PET/CT-derived radiomics-based machine learning models for differentiating maligna...

Current Treatment Options and Emerging Technologies for Pelvic Bone Tumors: From Limb Salvage to Precision Oncology.

In our practice, the treatment of pelvic bone tumors should begin with a multidisciplinary sarcoma-board evaluation that integrates biopsy-proven hist...

Recent progress in clinical and molecular biological research in rectal serrated lesions.

Colorectal cancer ranks among the most common malignancies worldwide. Rectal serrated lesions represent a significant precancerous condition, accounti...

Advancing cancer detection and treatment using longitudinal routine clinical data.

Cancer management remains fragmented across its continuum, from late-stage diagnosis and salvage therapies to non-personalized surveillance. Here, we ...

DNA methylation profiling enables subclassification of mucinous ovarian carcinoma and distinguishes it from extraovarian mucinous metastases.

Mucinous ovarian carcinoma (MOC) is an epithelial ovarian cancer subtype that is frequently misclassified as extraovarian mucinous metastasis (EOM) be...