Other Cancers

Multimodal machine learning models for predicting remission in major depressive disorder using clinical data, blood biomarkers, and DNA methylation.

Major depressive disorder (MDD) is a leading global health burden, yet only one-third of patients achieve remission with initial antidepressant therapy. Inflammatory biomarkers and epigenetic signatures such as DNA methylation have been implicated in treatment response, but their temporal predictive utility remains unclear. We analyzed 821 Korean patients with MDD from the MAKE BETTER study, integ...

Detection of esophageal varices and prediction of hepatic decompensation in unresectable hepatocellular carcinoma using AI.

BACKGROUND & AIMS: In hepatocellular carcinoma (HCC) with cirrhosis, portal hypertension worsens outcomes. Esophagogastroduodenoscopy (EGD), the current screening method for esophageal varices (EVs), is invasive and may delay therapy. We aimed to develop and externally validate non-invasive models to detect EVs and predict hepatic decompensation (bleeding, ascites or hepatic encephalopathy), a maj...

A systems approach identifies MERTK as a therapeutic vulnerability in ZFTA-RELA-driven ependymomas.

Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intracranial tumors in children and 4% in adults. Despi...

Toward Integration of Molecular Measures and Artificial Intelligence-Based Assessments With Clinical End Points in Inflammatory Bowel Disease.

Multimodal profiling of inflammatory bowel disease (IBD) patient tissue and blood samples has revealed the disease spectrum in unprecedented detail, a...

Development and validation of a prognosis model for low-grade gliomas based on metabolic gene risk scoring and immune microenvironment interaction.

PURPOSE: Low-grade gliomas(LGGs) show significant clinical and molecular heterogeneity, complicating progression prediction with conventional indicato...

Identifying Post-Surgical Recurrence Subtype of T1 Stage Colorectal Cancer by Machine Learning.

INTRODUCTION: Traditional risk stratification heavily relies on expert judgment and manually established thresholds. This study aims to automatically ...

Predicting renal-cell carcinoma recurrence after partial nephrectomy: a CT-radiomics approach.

BACKGROUND: About 30-40% of patients with renal-cell carcinoma experience recurrence within 5 years after partial nephrectomy despite current prognost...

A novel integrative machine learning-based prognostic model reveals lactylation regulation in hepatocellular carcinoma progression.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant liver tumor with poor clinical outcomes. Accumulated evidence has demon...

Health-oriented sleep states: making sleep states reflect health conditions.

STUDY OBJECTIVES: The rich information in sleep offers insights into brain function and overall health. The current guidelines for sleep staging by th...

Integrative bioinformatics and experiments identify RIBC2 as a key regulator in the esophageal cancer.

Early detection of esophageal cancer (EC) remains a major challenge due to the limited understanding of its initial molecular alterations. Therefore, ...

Magnetic resonance imaging (MRI) of the myometrium - benign and malignant disease.

Myometrial lesions are a common indication for pelvic imaging, with accurate characterisation crucial for guiding management. While ultrasonography re...

Development of a hybrid deep learning-based framework for liver fibrosis classification using ultrasound images.

BACKGROUND AND AIMS: Liver fibrosis is a progressive accumulation of extracellular matrix proteins with distortion of hepatic architecture and can pro...

Prediction of malignancy and metastasis of thyroid cancer by combined feature sets through advanced machine learning.

Periodontal bone loss analysis via keypoint detection with heuristic post-processing.

OBJECTIVES: This study proposes a deep learning framework and an annotation methodology for the automatic detection of periodontal bone loss landmarks...

Enhancing therapeutic outcomes with artificial intelligence for HR-positive, HER2-negative metastatic breast cancer.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) are an integral first-line treatment for hormone receptor-positive metastatic breast cancer, though r...

Randomized controlled trials in valvular heart disease: the evolving role of multimodality imaging.

Valvular heart disease represents a significant global health burden, with an estimated prevalence of 2.5% in high-income countries and projected incr...

Deep Learning Identification of Clear Cell Renal Cell Carcinoma on MR Imaging.

OBJECTIVE: To investigate the performance of various convolutional neural networks (CNNs) in identifying clear renal cell carcinoma (ccRCC) on MRI and...

Data-Driven Deciphering Structure-Mössbauer Spectroscopy Relationships in Iron-Based Compounds.

Accurate identification of material structures is crucial for establishing reliable structure-property relationships, yet this task is often hindered ...

Redefining Tumor Vascular Permeability through Deep Learning-Guided Microneedle Delivery.

Low-permeability (LP) tumor vasculature constitutes a major barrier to efficient nanomedicine delivery, making quantitative assessment and mechanistic...

Integrative analysis of immune and microbial subtypes predicts immunotherapy response in stomach adenocarcinoma.

The tumor immune microenvironment and intratumoral microbiota play critical roles in cancer progression and immunotherapy response, yet their integrat...