Other Cancers

Interpretable machine learning model for predicting operative difficulty in robotic total mesorectal excision for mid-low rectal cancer.

Precise preoperative prediction of surgical complexity in robot-assisted total mesorectal excision (R-TME) is essential for optimizing surgical strategies. The current study aimed to construct an interpretable machine learning (ML) model to anticipate operative difficulty in sphincter-preserving R-TME. Retrospective data from 449 patients diagnosed with mid-to-low rectal cancer undergoing R-TME at...

A risk stratification framework based on ammonia-induced cell death signatures for prognostic assessment and therapeutic insights in colorectal cancer.

BACKGROUND: Ammonia, which was traditionally regarded as a metabolic by-product, has more recently emerged as a crucial regulator of tumor metabolism and immune dysfunction. Nevertheless, the prognostic implications and therapeutic significance of ammonia-related genes in colorectal cancer (CRC) are still largely uncharted territory. This lack of exploration means that there is a significant gap i...

Unveiling the Impact of Copper Metabolism on Epithelial-Mesenchymal Transition of Triple-Negative Breast Cancer: Identification of Therapeutic Targets.

Triple-negative breast cancer (TNBC) is a biologically aggressive subtype of breast cancer marked by high heterogeneity and poor prognosis. Copper met...

Population-Level Raman Biochemical Staging of Malaria in Human Red Blood Cells Using Interpretable Machine Learning.

Accurate malaria staging is vital for treatment decisions and monitoring of transmission. Because mature Plasmodium falciparum parasites sequester in ...

An artificial intelligence model for prediction of hepatocellular carcinoma risk in patients with chronic hepatitis C.

Hepatocellular carcinoma (HCC) still occurs in patients with hepatitis C who achieved sustained virologic response (SVR) after direct-acting antiviral...

Conditional survival patterns and individualized prognostic prediction in malignant peritoneal mesothelioma.

Malignant peritoneal mesothelioma (MPM) is a rare, aggressive cancer with limited treatment options and extremely poor survival outcomes. Due to the d...

Application of delta radiomics based on cone-beam computed tomography in predicting radiotherapy efficacy for nasopharyngeal carcinoma.

PURPOSE: To investigate the value of cone-beam computed tomography (CBCT)-based delta radiomics for predicting short-term radiotherapy (RT) response i...

Direct Quantification of Uncertainty in Deep Learning-Based Automatic Sleep Staging.

OBJECTIVE: To evaluate and compare different methods for quantifying uncertainty in deep learning-based automatic sleep staging, thereby enhancing tra...

Molecular Pathology of Soft-tissue Neoplasms.

Soft-tissue tumors are rare mesenchymal neoplasms characterized by extensive morphologic and genetic heterogeneity. Advances in molecular pathology ha...

From Theory to Practice: Which Biomarkers Are Ready for Predicting Response in Advanced HCC?

Systemic therapies for advanced hepatocellular carcinoma (HCC) have expanded considerably with the advent of tyrosine kinase inhibitors, immune checkp...

Enhancing urothelial carcinoma diagnosis with artificial intelligence-integrated urine cytology: Biopsy-validated accuracy and efficiency gain.

BACKGROUND: Urine cytology is a noninvasive tool for detecting urothelial carcinoma, yet its performance depends heavily on expert cytologists and tim...

Development of an exploratory prediction model for preoperative CK19 expression in esophageal cancer driven by radiomics and machine learning.

BACKGROUND: Esophageal cancer ranks among the most lethal malignancies worldwide, particularly prevalent in the Guangdong-Chaoshan region of China due...

Automatic framework for PD-L1 expression evaluation in Latino patients with non-small cell lung cancer.

Programmed death ligand-1 (PD-L1) expression is a key biomarker for identifying non-small cell lung cancer (NSCLC) patients eligible for immunotherapy...

Morpho-functional plasticity of tumour-associated macrophages: linking cell shape, ultrastructure, and immune regulation in cancer.

Macrophages are highly adaptable immune cells that play dual roles in the tumor microenvironment (TME), either promoting or restraining tumor progress...

Neoadjuvant Immunotherapy in Locally Advanced Head and Neck Squamous Cell Carcinoma: From Oncologic Outcomes to Response-Adaptive Treatment De-escalation.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) are associated with poor 5-year survival and substantial treatment-related morbidity. Neoadj...

Rapid autofluorescence based 3D optical imaging of the pancreatic cancer milieu at mesoscopic scale - stain-free volumetric segmentation.

Although major advances have been made in the field of mesoscopic imaging and associated tissue clearing protocols, these applications are greatly cha...

Explainable artificial intelligence in prostate cancer treatment recommendation: A decision support system for oncological expert panels.

BACKGROUND: Therapeutic decisions in clinical oncology are commonly established through interdisciplinary consensus in multidisciplinary cancer confer...

Spatially resolved single cell analysis suggests an APOE NCF1 associated immunosuppressive niche and its prognostic signature in thyroid cancer.

BACKGROUND: Thyroid carcinoma (TC) presents a rising global incidence, with a subset of cases progressing aggressively despite standard therapies. The...

Integrating machine learning and spatiotemporal transcriptomics to build a diagnostic model for osteosarcoma metastasis and to decipher the role of necroptosis genes.

OBJECTIVE: To develop a diagnostic model for osteosarcoma metastasis and elucidate the spatiotemporal role of necroptosis genes. METHODS: Multi-omics ...

Techniques and outcomes review of the endoscopic management of gastrointestinal bleeding.

INTRODUCTION: Gastrointestinal (GI) bleeding is a frequent and potentially life-threatening emergency that imposes a substantial healthcare burden wor...