Oncology/Hematology

Complex biological systems analysis and deep learning for prognostic prediction of esophageal squamous cell carcinoma.

Esophageal squamous cell carcinoma (ESCC) prognosis remains poor, and traditional models often fail to capture complex nonlinear interactions between clinical and molecular features. We integrated transcriptomic data from public datasets and an independent clinical cohort to identify prognostic biomarkers. Using weighted gene co-expression network analysis (WGCNA) and Lasso-Cox regression, we iden...

A cell comparative multiple instance learning network guided by image quality assessment for cervical whole slide image classification.

Early screening is essential for reducing the incidence and mortality of cervical cancer, and artificial intelligence-based analysis of whole slide images (WSIs) enables large-scale automated screening. However, existing methods often ignore image quality variations and inter-individual morphological differences, which limits their robustness in clinical settings. This study proposes a quality-awa...

Small but mighty: Peptides as next-generation immunotargeting agents in gynecological cancers.

The most common cancers in women, ovarian, cervical and endometrial, are still a significant cause of cancer-related illness and death around the worl...

Ultrasonographic Evaluation of Pediatric Thyroid Nodules: Adult Risk Stratification Systems, 2021 K-TIRADS Revision, and Future Refinements.

Although pediatric thyroid cancer is rare, it has characteristics distinct from those of adult thyroid cancer. Thyroid nodules in children present a h...

Commercial Artificial Intelligence (AI) Tool for Screening Digital Breast Tomosynthesis: Factors Associated With AI-Based Breast Cancer Detection.

BACKGROUND. Research on artificial intelligence (AI)-based computer-assisted detection and diagnosis (CADe/CADx) algorithms has focused primarily on d...

Risk-Stratified Biologic Efficacy in Ulcerative Colitis: A Multicenter Machine Learning Study.

BACKGROUND: Ulcerative colitis (UC) exhibits a heterogeneous clinical course, complicating prognostication and therapeutic decision making. Current to...

Bringing AI to Cancer's Regulatory Genome.

A new AI model that predicts how noncoding DNA mutations alter gene regulation is helping cancer researchers identify which genetic changes drive tumo...

[Contrast-enhanced CT-based habitat radiomics for analyzing the predictive capability for oral squamous cell carcinoma].

OBJECTIVES: By comparing deep learning and habitat analysis models based on contrast-enhanced CT (CECT), this study explores a novel approach to predi...

A Thermogalvanic Cell Microneedle Patch for Integrated Diagnosis and Treatment of UV-Induced Early Skin Cancer.

Early stage skin cancer exhibits a high cure rate; however, conventional noninvasive screening suffers from diagnostic inaccuracies, and treatment rel...

Follow-Up Bias in Tumor Dynamic Modeling: A Comparison of Classical and Neural-ODE Approaches.

Tumor dynamic models are vital for evaluating oncology treatments and guiding clinical drug development decisions. However, few studies rigorously ass...

Rapid screening of potent and mechanistically insightful repurposable anticancer drugs targeting EGFR for non-small cell lung cancer: machine learning-aided and structure-guided approach.

Despite the initial success of EGFR-targeted therapies in non-small cell lung cancer (NSCLC), the emergence of drug resistance remains a significant c...

Mechanistic Topology of Notopterygium incisum Essential Oil against Rheumatoid Arthritis: Machine Learning-Guided CASP1 Screening and Nanoemulsion Evaluation.

OBJECTIVE: To elucidate the anti-rheumatoid arthritis (RA) mechanisms of Notopterygium incisum essential oil (NIEO) using an integrated strategy combi...

mRNA vaccines in cancer immunotherapy: current progress and perspectives in solid tumors and hematologic malignancies.

The unprecedented success of mRNA vaccines during the COVID-19 pandemic has accelerated the development of nucleic acid-based therapeutics, particular...

Factors Influencing Universal Coverage of AI-Assisted Cervical Cancer Screening: Qualitative Study Based on the Macro Model of Health System.

BACKGROUND: Improving screening coverage is a central goal of the global strategy to eliminate cervical cancer. In resource-constrained settings, insu...

Performance of Large Language Models vs Conventional Machine Learning for Predicting Clinical Outcomes With Limited Data: Comparative Study.

BACKGROUND: Machine learning (ML) can be used to predict clinical outcomes. Training predictive models typically requires data for hundreds or thousan...

Multimodality treatment and survival in primary cardiac malignancies: evidence from competing-risk and machine learning analyses.

BACKGROUND: Primary cardiac malignancies are rare and highly aggressive, with limited clinical evidence to guide optimal treatment. This study evaluat...

Deep learning framework for predicting EGFR mutation status from H&E whole slide images in lung adenocarcinoma.

From prediction to precision: how immunopeptidomics advances neoantigen discovery.

T cell recognition of peptides presented by class I and II human leukocyte antigen (HLA) molecules is fundamental to cancer immunity and personalized ...

Deep learning model for pathological invasiveness prediction using smartphone-based surgical resection images in clinical stage IA lung adenocarcinoma (SuRImage): a prospective, multicentric, diagnostic study.

BACKGROUND: In clinical stage IA lung adenocarcinoma (LUAD), rapid and accurate intraoperative diagnosis is crucial to decide whether to perform segme...

Integrating Bulk RNA-Seq and Spatial Transcriptomics Data to Reveal Distinct Immune Escape Mechanism and Immunotherapy Based on Post-Translational Modification in Head and Neck Squamous Cell Carcinoma.

Post-translational modification (PTM) plays a crucial role in head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic...