Other Cancers

Toward a Synthetic Data Revolution: Diffusion Model-Enhanced Hepatocellular Carcinoma Prediction in Steatotic Liver Disease.

AIM: Steatotic liver disease (SLD) encompasses a heterogeneous spectrum with varying risks of hepatocellular carcinoma (HCC). Limited sample sizes limit the development of predictive models, particularly for rare outcomes. This study evaluated whether generative artificial intelligence (AI)-based synthetic data augmentation can enhance HCC risk prediction in SLD patients. METHODS: A random surviva...

Impact of nanocarrier mediated drug delivery systems: a deep dive into therapeutics and clinical management of breast cancer.

Breast cancer (BC) is the most frequently diagnosed malignancy and the leading cause of cancer-related death among women worldwide. The therapeutic limitations of conventional treatment modalities are due to systemic toxicity, multidrug resistance (MDR), and poor tumor specificity. Nanocarrier-based drug delivery systems (liposomes, polymeric nanoparticles, dendrimers, and lipid nanocarriers) hold...

Externally Tested AI Models for Malignancy Classification of Lung Nodules at Chest CT: A Systematic Review and Meta-Analysis.

Purpose To evaluate the pooled diagnostic accuracy of externally tested AI models for malignancy classification of lung nodules on chest CT. Materials...

A new era beckons in asthma: enhanced models of care, disease remission, artificial intelligence and consumer participation.

The landscape of asthma management is undergoing significant transformation. This change is driven by several factors: deeper understanding of asthma ...

Multiparametric MRI-Based Habitat Radiomics Combined with Deep Transfer Learning for Predicting Extrathyroidal Extension in Papillary Thyroid Carcinoma.

The objective of the study is to develop and validate a multiparametric MRI (mpMRI)-based model that integrated with habitat-based radiomics, deep tra...

A multimodal prediction framework for colorectal cancer peritoneal metastasis: CT-based tumor and adipose tissue analysis.

Accurate preoperative assessment of CT-occult peritoneal metastasis (PM) in colorectal cancer is critical for clinical decision-making. This study dem...

Biomarker-driven and AI-assisted nanomedicine for breast cancer: advancing precision drug delivery from bench to bedside.

INTRODUCTION: Breast cancer remains the most prevalent malignancy among women worldwide, with its pronounced molecular heterogeneity demanding therape...

Cytoreductive nephrectomy improves survival in metastatic papillary renal cell carcinoma: a population-based study with machine learning validation and landmark analysis.

BACKGROUND: The role of cytoreductive nephrectomy (CN) in metastatic papillary renal cell carcinoma (pRCC) remains poorly defined, as most CN evidence...

A multimodal deep learning model predicting hyperprogressive disease for PD-1 blockade in advanced hepatocellular carcinoma.

Immune checkpoint inhibitors, particularly antibodies targeting programmed cell death 1 (PD-1), are increasingly used for advanced hepatocellular carc...

An integrated machine learning and mendelian randomization approach identifies SERPING1 as a prognostic biomarker associated with CD8 + T-cell infiltration in DLBCL.

BACKGROUND: SERPING1, which encodes the C1 inhibitor (C1-INH) of the complement system, and plays a key regulator in regulating inflammatory responses...

Machine learning based prediction of recurrence in oral tongue cancer: a systematic review with quantitative synthesis.

PURPOSE: Oral tongue squamous cell carcinoma (OTSCC) is characterized by aggressive local invasion and a high risk of cervical nodal metastasis and mo...

Deep learning-based cross-modal MR-CT registration for brain metastases radiotherapy with multi-scale feature refinement and brainstem guidance.

Accurate multimodal deformable registration between magnetic resonance (MR) and computed tomography (CT) images is essential for precise target deline...

Evaluating the Performance of Large Language Models on Palliative Care Test Questions: A Mixed Methods Study.

BACKGROUND: Little is known about large language model (LLM) performance on palliative care (PC)-related knowledge-based tasks. We evaluated two LLMs ...

ViGNet: A clinical data-supported deep learning approach for NSCLC immunotherapy response prediction in digital pathology.

Histopathology is the cornerstone of oncology diagnosis, while whole-slide images (WSIs) enable the transition to digital, quantitative pathology. Lev...

Deep learning-based automated assessment of pulmonary artery indices and surgical approach triage for tetralogy of Fallot from multicenter cardiac computed tomography (CT).

AIM: To develop an automated framework for deep learning (DL)-based segmentation, pulmonary artery indices (PAIs) computation, and rule-based surgical...

Prospective germline exome and machine learning-based risk score identify predictive and prognostic biomarkers of immunotherapy outcomes in advanced non-small cell lung cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). However, a su...

Translating lineage-resolved single-cell programs to bulk clinical prognosis: Adversarial generative learning reveals lineage-informed immune - stromal - epithelial risk signatures.

BACKGROUND: Breast cancer transcriptional programs span malignant epithelial cells, and the tumor microenvironment (TME), yet tumor-normal contrasts a...

Robust end-to-end stratification of amyotrophic lateral sclerosis patients via recurrent variational autoencoder and consensus clustering.

OBJECTIVE: This study aims to develop a data-driven methodology for stratifying Amyotrophic Lateral Sclerosis (ALS) patients based on longitudinal dis...

Immune cell delivery platforms for tumor therapy: From empirical approaches to AI-integrated frameworks.

The heterogeneity and immunosuppressive characteristics of the tumor microenvironment present significant challenges to traditional treatment strategi...

Nanomedicine in precision treatment of gastric cancer: current clinical landscape.

Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with therapeutic efficacy often hindered by late-stage diagnosis, c...