Other Cancers

Prediction of 12-Week Remission in Patients With Depressive Disorder Using Reasoning-Based Large Language Models: Model Development and Validation Study.

BACKGROUND: Depressive disorder affects over 300 million people globally, with only 30% to 40% of patients achieving remission with initial antidepressant monotherapy. This low response rate highlights the critical need for digital mental health tools that can identify treatment response early in the clinical pathway. OBJECTIVE: This study aimed to evaluate whether reasoning-based large language m...

Sorafenib nanomedicine in HCC: nano-bio interactions and combination therapies.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with systemic therapies offering only limited benefit. Sorafenib, the first-line multi-kinase inhibitor, is constrained by poor pharmacokinetics, dose-limiting toxicities, and the rapid emergence of resistance. Nanotechnology-based drug delivery systems (NDDS) provide promising strategies to address these...

Prediction of renal cell carcinoma: Development and validation of machine learning model.

Renal cell carcinoma (RCC) is the leading cause of urinary system morbidity and mortality. Early identification is crucial for improving RCC patient o...

An exploratory study on the relationship between renal cell carcinoma and CAFs infiltration by integrating Pathomics and collagen features.

OBJECTIVE: Cancer-associated fibroblasts (CAFs) are a critical component of the tumor microenvironment and play a significant role in renal cell carci...

Diagnostic Performance of Preoperative Imaging-based Radiomics Models for Predicting Liver Metastases in Colorectal Cancer: A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of preoperative computed tomography (CT) and magnetic resonance imaging (MRI)-based r...

Deep learning-derived CT body composition enhances survival risk stratification beyond the TNM system in locally advanced gastric cancer: a multi-modality cohort study.

BACKGROUND: Survival outcomes in locally advanced gastric cancer remain heterogeneous despite standard treatment and outcome classifications. Visceral...

Coriandrum sativum improves prognosis in clear cell renal cell carcinoma by targeting NEK6 to modulate the immune microenvironment: a predictive study based on network pharmacology and multi-omics analysis.

Coriandrum sativum L. (coriander) is a medicinal herb with diverse pharmacological properties, but its molecular mechanism in clear cell renal cell ca...

Improved screening for pulmonary Kaposi sarcoma in a low-resource setting.

OBJECTIVE: The lung is commonly involved in advanced Kaposi sarcoma (KS) but diagnosis of pulmonary KS in low-resource settings is difficult. Clinical...

Efferocytosis-associated transcriptomic patterns characterize prognosis and immune landscape in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents, characterized by high heterogeneity and poor prognosis. ...

Spatial transcriptional profiling of CHB liver biopsies reveals an undetected population of zonally biased HBV-integrated cells.

BACKGROUND & AIMS: HBV covalently closed circular DNA (cccDNA) and HBV-integrated DNA (iDNA) are features of chronic HBV (CHB). Elimination of both ce...

Haar-initialized parametric wavelet compression with attention-driven lightweight CNN for brain tumor classification on edge devices.

This paper presents a lightweight hybrid framework that integrates a Haar-initialized Parametric Wavelet Transform (PWT) with a Convolutional Neural N...

The Future of Non-muscle-invasive Bladder Cancer: Towards a Molecular-Digital Paradigm for Personalized Management.

The management of non-muscle-invasive bladder cancer (NMIBC) is undergoing a major paradigm shift driven by molecular biomarkers, artificial intellige...

Incidence and implications of abstinence-induced recompensation in alcohol-related cirrhosis.

BACKGROUND & AIMS: Alcohol abstinence enables hepatic recompensation in patients with decompensated alcohol-related cirrhosis. This study investigated...

Machine learning-based prediction of central lymph node metastasis in unifocal papillary thyroid microcarcinoma.

OBJECTIVE: This study aims to develop a machine learning (ML) model to predict the risk of central lymph node metastasis (CLNM) in patients with papil...

Immune Checkpoint Activity and Prognostic Roles of TNFRSF8, CD160, and TNFSF9 in Primary and Brain Metastatic NSCLC.

Here, we utilized advanced bioinformatics approaches alongside experimental validation to identify key prognostic biomarkers and potential immune chec...

ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning.

Co-fractionation mass spectrometry (CF-MS) enables large-scale profiling of endogenous protein-protein interactions, yet CF-MS data generation is of l...

A deep learning radiopathomic signature predicts recurrence risk of hepatocellular carcinoma after hepatectomy.

Accurate prediction of recurrence risk after hepatectomy still remains a clinical challenge for hepatocellular carcinoma (HCC). We develop a deep lear...

Integrative multi-omics and machine learning framework identifies PRDX4 as a redox-EMT regulator and predictive marker in bone-metastatic breast cancer.

Bone metastasis is a major cause of morbidity and mortality in breast cancer, yet effective prognostic models and targeted therapies remain limited. H...

Review of flow cytometry findings and associated scoring approaches for identifying myelodysplastic syndrome and the future role of machine learning in improving the diagnostic algorithm.

OBJECTIVE: Myelodysplastic syndrome (MDS) is a heterogeneous set of neoplasms that require careful exclusion of potential mimics before diagnosis. In ...

Machine learning-assisted detection of canine mammary tumors using serum autoantibody signatures.

Canine mammary tumors (CMTs) are the most common neoplasms in intact female dogs, yet early detection remains challenging due to the lack of clinicall...