Other Cancers

Preoperative hypoalbuminemia predicts early complications, mortality, and discharge disposition following surgical resection of spinal metastases: a nationwide study.

PURPOSE: Patients undergoing surgery for spinal metastases often have limited physiologic reserve. Although hypoalbuminemia is a recognized risk marker, its graded association with short-term postoperative outcomes and discharge disposition has not been well defined in large national cohorts. We evaluated the relationship between preoperative serum albumin and early postoperative outcomes followin...

Predicting 5-Year Mortality in Non-Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development and Validation Study.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic prediction clinically essential. Machine learning models are increasingly used to assess prognosis; however, developing systems that combine high discrimination with clear, clinically interpretable reasoning remains challenging. OBJECTIVE: This study a...

The atlas of abdominal organ remodeling in hepatocellular carcinoma patients: An artificial intelligence-based multicenter imaging study.

BACKGROUND: Morphological changes of abdominal organs in hepatocellular carcinoma (HCC) remain uncharacterized. This study aimed to automatically quan...

Radiological Assessment of Liver and Biliary Neoplasms.

Primary liver cancer, encompassing hepatocellular carcinoma and cholangiocarcinoma, represents a growing global health burden with significant morbidi...

Integrative machine learning and multi-omics analysis reveals ATIC as a promoter of hepatocellular carcinoma progression.

Autophagy plays a non-negligible role in the progression and immune regulation of hepatocellular carcinoma (HCC). An integrated analysis of the autoph...

Deep learning layer-specific collagen quantification correlates with activity and is associated with outcomes in Crohn's disease.

BACKGROUND & AIMS: Intestinal fibrosis remains a major unmet need in inflammatory bowel disease (IBD). Although collagen deposition is the defining fe...

Predicting time to local failure after gamma knife radiosurgery for melanoma brain metastases using survival machine learning.

BACKGROUND: Melanoma brain metastases treated with Gamma Knife radiosurgery show heterogeneous local control trajectories. Accurate prediction of time...

Machine learning models predict the immunotherapy response in tumors on the basis of DNA methylation.

BACKGROUND: The epigenetic control of immune responses plays a crucial role in the development and progression of cancer. The need to identify biomark...

A histopathologically verified dataset of magnifying narrow-band imaging endoscopy for classifying the gastric precancerous cascade.

Gastric cancer is a leading cause of mortality worldwide, yet the development of computer-aided diagnosis (CAD) systems for its early detection is hin...

Development and validation of pathomics signature for predicting prognosis of advanced high-grade serous ovarian carcinoma patients after platinum-based chemotherapy.

In patients with advanced high-grade serous ovarian carcinoma (HGSOC), the standard treatment typically involves platinum-based chemotherapy after deb...

Ultrasound-based multiregional radiomics nomogram for predicting recurrence in HER2-positive breast cancer.

PURPOSE: Accurate prediction of recurrence risk is crucial for personalizing therapy in human epidermal growth factor receptor 2-positive (HER2-positi...

Single-cell transcriptomics and machine learning unveil liquid-liquid phase separation-related biomarkers in HPV-positive cervical cancer.

BACKGROUND: Liquid-liquid phase separation (LLPS) dysregulation is a key driver of oncogenesis, yet its specific role in HPV-positive cervical cancer ...

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment options for resectable non-small cell lung cancer ...

Multimodal Artificial Intelligence Prediction of Abiraterone Efficacy in Two STAMPEDE Phase 3 Trials of Non-Metastatic Very High-Risk Prostate Cancer.

BACKGROUND: Long-term androgen deprivation therapy (LT-ADT) with radiotherapy is standard-of-care for high-risk localized prostate cancer, with abirat...

Machine Learning-Guided Survival Prediction and Treatment Sequencing in Advanced Soft Tissue Sarcoma Beyond Second-Line Therapy: A Retrospective Cohort Study.

INTRODUCTION: Evidence guiding the optimal sequencing of later-line systemic therapy in advanced soft tissue sarcoma (STS) remains limited. The aim of...

Artificial intelligence in prostate cancer imaging: A mini-review of current applications and future directions.

This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and fu...

Hyperspectral Imaging for Breast-Conserving Surgery Margin Assessment: A Systematic Review.

CONTEXT.—: Breast-conserving surgery (BCS) offers comparable overall survival rates to mastectomy. However, 14% to 37% of cases require re-excision ow...

Targeting the intrinsically disordered AR-NTD through a machine learning-based enhanced sampling workflow.

Targeting the intrinsically disordered N-terminal domain of the androgen receptor (AR-NTD) represents a promising strategy to overcome resistance in p...

Deep learning based on multiparametric MRI for differentiating benign from malignant PI-RADS 3 prostate lesions: a dual-center study.

To address the diagnostic challenge of indeterminate PI-RADS 3 prostate lesions, we developed a non-invasive deep learning radiomics model using multi...

The SALV-Dataset Registry: An Expertly Curated Digital Clinicopathological Dataset for Salivary Gland Tumor Research and AI-Assisted Diagnostic Tools.

UNLABELLED: Salivary gland tumors are rare and morphologically diverse, posing both diagnostic and scientific challenges. This study presents the firs...