Oncology/Hematology

A Domain-Specific Pretrained Model for Detecting Malignant and Premalignant Ocular Surface Tumors: A Multicenter Model Development and Evaluation Study.

Malignant and premalignant ocular surface tumors (OSTs) can be sight-threatening or even life-threatening if not diagnosed and treated promptly. Artificial intelligence holds great promise for the early detection of these diseases. However, training traditional convolutional neural networks (CNNs) for this task presents challenges due to the lack of large, well-annotated datasets containing OST im...

The development of predictive biomarkers and immunologic markers for breast cancer: current status and future perspectives.

Breast cancer is the leading cause of cancer-related mortality among women worldwide. The development of predictive biomarkers and immunologic markers has revolutionized breast cancer diagnosis and treatment, enabling personalized medicine approaches. This study aims to review the current status, challenges, and future directions of predictive and immunologic biomarkers in breast cancer. Predictiv...

Editorial: Multiscale cancer modeling, oncology and digital (virtual) twins in the cancer domain.

Leveraging multiple cell-death patterns based on machine learning to decipher the prognosis, immune, and immune therapeutic response of soft tissue sarcoma.

Soft tissue sarcomas (STS) imposes a substantial healthcare burden on society. The progression of these tumors is significantly influenced by diverse ...

MobNas ensembled model for breast cancer prediction.

Breast cancer poses a real and immense threat to humankind, thus a need to develop a way of diagnosing this devastating disease early, accurately, and...

Multidimensional Evidence Chain of Nutritional Impact on Digestive System Tumors: Integration of Mendelian Randomization Causal Inference, NHANES Epidemiological Data, and Transcriptomic Analysis.

BACKGROUND: The global burden of digestive system tumors (e.g., hepatocellular carcinoma, gastric cancer, colorectal cancer) continues to rise, with l...

Skeletal Muscle Density as a Predictive Marker for Pathologic Complete Response in Triple-Negative Breast Cancer Treated with Neoadjuvant Chemoimmunotherapy.

: The predictive value of muscle-related indicators in triple-negative breast cancer (TNBC) patients undergoing neoadjuvant chemotherapy (NAC) remains...

Machine learning-based radiomics analysis in enhancing CT for predicting pathological subtypes and WHO staging of thymic epithelial tumors: a multicenter study.

This study is aimed to develop predictive models for classifying thymic epithelial tumor (TET) histological subtypes (A/AB/B1, B2/B3, C) and WHO stage...

Extrachromosomal circular DNA drives dynamic genome plasticity: emerging roles in disease progression and clinical potential.

Extrachromosomal circular DNA (eccDNA) has emerged as a dynamic and versatile genomic element with key roles in physiological regulation and disease p...

Evaluation of locoregional invasiveness of early lung adenocarcinoma manifesting as ground-glass nodules via [Ga]Ga-FAPI-46 PET/CT imaging.

PURPOSE: Accurate differentiation of the histologic invasiveness of early-stage lung adenocarcinoma is crucial for determining surgical strategies. Th...

Epidemiology and survival of patients with primary lymphoma of bone: a large retrospective cohort study.

Primary lymphoma of bone (PLB) is a rare extranodal lymphoma, and its epidemiology and prognosis remain controversial. We conducted a retrospective an...

Unraveling the significance of cuproptosis in hepatocellular carcinoma heterogeneity and tumor microenvironment through integrated single-cell sequencing and machine learning approaches.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits pronounced heterogeneity, which significantly limits the effectiveness of precision therapies. A c...

Prognostic model identification of ribosome biogenesis-related genes in pancreatic cancer based on multiple machine learning analyses.

BACKGROUND: Pancreatic cancer is a highly aggressive cancer characterized by low survival rate. Enhanced ribosome biogenesis may be associated with tu...

Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.

Skin cancer is one of the most prevalent malignant tumors, and early detection is crucial for patient prognosis, leading to the development of mobile ...

National Guidelines for Cytoreductive Surgery and Hyperthermic Intraperitoneal Chemotherapy (HIPEC) in Peritoneal Malignancies: A Worldwide Systematic Review and Recommendations of Strength Analysis.

BACKGROUND: National guidelines (GLs) for surgical cytoreduction (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) in the management of peri...

Integrative multi-omics reveal NSUN2 facilitates glycolysis and histone lactylation-driven immune evasion in renal carcinoma.

Clear cell renal carcinoma (ccRCC) is the most prevalent and aggressive subtype of kidney cancer. Targeting ccRCC metabolism is a promising therapeuti...

Explainable machine learning and feature interpretation to predict survival outcomes in the treatment of lung cancer.

The treatment outcomes of lung cancer are highly variable, and machine learning (ML) models provide valuable insights into how clinical and biochemica...

Multimodal Explainable Artificial Intelligence for Prognostic Stratification of Glioblastoma Patients.

Glioblastoma is the most common and aggressive malignant adult tumor of the central nervous system, with a grim prognosis and heterogeneous morphologi...

Role of machine learning in molecular pathology for breast cancer: A review on gene expression profiling and RNA sequencing application.

INTRODUCTION: Breast cancer is the most prevalent cancer among women, with growing incidence and mortality rates. Regardless of remarkable progress in...

Role of artificial intelligence in cancer drug discovery and development.

The role of artificial intelligence (AI) in cancer drug discovery and development has garnered significant attention due to its potential to transform...