Other Cancers

Network toxicology and multi-omics analyses identify diagnostic genes and elucidate underlying mechanisms of 6PPDQ-induced hepatocellular carcinoma.

With the rapid expansion of tire production, the antioxidant N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine (6PPD) and its transformation product, 6PPD-quinone (6PPDQ), have emerged as widespread environmental contaminants with demonstrated toxicity. Here, we employed an integrated network toxicology and computational framework to elucidate the mechanisms by which 6PPDQ may contribute to hepat...

Preoperative prediction of lymph node metastasis and prognosis in gastric cancer patients: A machine learning model based on 18F-FDG metabolic parameters.

OBJECTIVE: To construct and validate a model for predicting lymph node metastasis (LNMs) of gastric cancer (GC) based on 18F-FDG PET/CT multi-parameter data and multiple machine learning (ML) algorithms. METHODS: We conducted a retrospective analysis of clinical records and 18F-FDG PET/CT images from 167 GC patients treated with radical gastrectomy. The dataset was randomly divided into two cohort...

Metabolic-immune interactions in gastric cancer T cells: A single-cell atlas for prognostic biomarker identification.

Metabolic alterations and immune dysfunction within the gastric tumor microenvironment critically drive gastric cancer (GC) progression and therapeuti...

Plasma metabolomics identifies lipid mediators linking depression and cognitive decline in late-life depression.

BACKGROUND: Late-life depression (LLD) features recurrent episodes and frequently co-exists with cognitive impairment, which predicts worse outcomes a...

Predicting Postoperative Discharge Status and Readmissions in Spinal Metastatic Disease Using Machine Learning Models.

Operative management of spinal metastatic disease is largely for symptom palliation rather than curative and revolves around the expectation that post...

Neural Latent Filtering for Gene Discovery in Breast Cancer Subtypes.

Gene selection from expression data represents a challenging task, primarily due to the high data dimensionality and the vast number of genes that wou...

Degraders on Demand: Engineering Smart Nanocarriers for PROTAC Delivery.

Proteolysis-targeting chimeras (PROTACs) are transforming targeted therapeutics by enabling the selective and catalytic degradation of disease-associa...

A Multimodal Large Language Model Framework for Clinical Subtyping and Malignant Transformation Risk Prediction in Oral Lichen Planus: A Paired Comparison With Expert Clinicians.

BACKGROUND: Oral lichen planus (OLP), oral lichenoid lesions (OLL), and squamous cell carcinoma on a lichenoid background (SCC-over-LP/LLP) overlap cl...

Revolutionizing early detection of TNBC: The rise of non-invasive biomarkers and next-gen diagnostic strategies.

Triple negative breast cancer (TNBC) is the most malignant subtype of breast cancer (BC), which accounts for 10-20 % of BC incidences, and its early d...

Hitting the Bull's AI: Artificial Intelligence-derived Imaging Features and their Association with Outcomes in CT-guided Lung Biopsy, a Retrospective Study.

PURPOSE: This study aims to evaluate whether quantitative imaging features analyzed by an artificial intelligence (AI) tool are associated with succes...

Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.

The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...

AI Clinical Decision Tools in Multidisciplinary Team Discussions for Colorectal Cancer.

Multidisciplinary team (MDT) discussions have become a cornerstone of colorectal cancer (CRC) management, integrating the expertise of surgeons, oncol...

Deep-learning/transfer-learning based Overall Survival prediction conditional on Progression-Free Interval with TCGA RNA-seq expression and KEGG-pathways.

We developed a novel deep-learning network that integrated Progression-Free Interval (PFI) as a condition based on transfer learning and fine tuning, ...

Artificial Intelligence as a Prognostic Tool in Cardiac Amyloidosis: A Review.

Cardiac amyloidosis (CA) poses a significant prognostic challenge due to its varied presentations and frequent delays in identification. While traditi...

Machine Learning-Based Multi-Omics Integration for Identification of Hepatocellular Carcinoma Biomarkers in an Egyptian Cohort.

Hepatocellular carcinoma (HCC) ranks among the most common causes of cancer-related deaths globally. The high incidence of HCC is largely linked to ch...

Artificial Intelligence for the Treatment and Management of Colorectal Liver Metastases.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy worldwide. Prognosis is significantly worsened in patients with colorectal liv...

Machine learning-assisted prognosis of multiple myeloma side population cells via SRGs and OCLR stemness index.

BACKGROUND AND OBJECTIVE: Relapse in Multiple Myeloma, driven by therapy-resistant cancer stem cells, necessitates the development of more specific an...

Multi-cancer framework with cancer-aware attention and adversarial mutual-information minimization for whole slide image classification.

Whole Slide Images (WSIs) are crucial in modern pathology, offering high-resolution data for accurate diagnosis, treatment planning, and research. Dee...

Dermoscopy-guided high-frequency ultrasound: Principles and applications in dermatology.

Conventional skin imaging modalities are often bulky, expensive, and impractical for routine dermatology practice. There is a need for a portable, mul...

A Deep Learning-Based Multimodal Clinico-Histology-Genomic Prognostic Model in Prostate Cancer.

BACKGROUND: Prostate cancer remains a leading cause of cancer mortality, yet current risk stratification systems inadequately integrate multidimension...