Other Cancers

Malignant vs. Non-malignant Annotations on TCGA Breast Cancer Whole Slide Images for AI Analysis.

Identification of malignant and non-malignant regions in breast cancer whole slide images (WSIs) is essential for understanding tumor heterogeneity and histopathological evaluation. Annotated data allows deep learning models to learn features and analyze histological structures. In this study, we obtained 50 breast cancer WSIs from The Cancer Genome Atlas (TCGA) and had an expert pathologist manua...

Multimodal AI-driven analysis in breast and lung cancer: insights from the OPTIMA prototyping workshop.

This paper reports on insights from the OPTIMA (Optimal Treatment for Patients with Solid Tumours in Europe Through Artificial Intelligence) prototyping workshop held in Berlin from November 6 to November 8, 2024. Through integrated analysis of clinical, genomic, imaging and pathology data, we addressed the following key challenges in breast and lung cancer management: utility of comprehensive gen...

Photon-counting Detector CT Spectral Reconstructions for Radiomics-based Liver Lesion Classification: A Multicenter Study.

OBJECTIVES: Accurate noninvasive classification of hepatic lesions remains a diagnostic challenge, particularly on conventional CT. Photon Counting De...

Integrated spatial transcriptomics and pan-cancer XGBoost modeling uncover spatial drivers of immune exclusion and predict immunotherapy response.

Immunotherapy has revolutionized cancer treatment, yet characterizing the spatial complexity of the tumor immune microenvironment remains a challenge....

Utilizing natural language processing (NLP) to identify breast cancer-associated lung metastases from pathology reports to delineate characteristics of this site of recurrence.

PURPOSE: Natural language processing (NLP, artificial intelligence) can enable automated identification of records in large datasets. The purpose of t...

Multimodal AI model for early detection of hepatocellular carcinoma.

Detection of early hepatocellular carcinoma (eHCC) is important for timely treatment and improved prognosis. However, it is challenging to distinguish...

Polymer Drug Conjugate: A Revolution in Drug Delivery.

Polymer-drug conjugates (PDCs) represent a remarkable advancement in modern medicine, leveraging the physicochemical properties of polymers to enhance...

LCPBert: ProtBERT-based early-stage lung cancer prediction from T cell receptor beta sequences.

Early detection of lung cancer remains challenging due to limitations of current methods. We developed LCPBert, a deep learning framework leveraging p...

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 ...

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...

[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...

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...

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...

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...

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 ...

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...

Higher Diagnostic Accuracy of an AI Model for Colposcopy Compared With Conventional and Digital Colposcopic Evaluation.

OBJECTIVE: Colposcopy involves subjective visual assessment of cervical features that may indicate cervical dysplasia. Pattern recognition during colp...