Other Cancers

IGH::FENDRR and specific KRAS mutations define a novel B-ALL molecular subtype with poor chemotherapy response.

Large scale sequencing efforts have defined up to 27 diagnostic entities in B-ALL, leaving few samples without subtype assignment. Extended genomic and transcriptomic profiling in routine diagnostics broadens the sample collection and holds the potential to identify novel B-ALL subtypes. By analyzing an aggregated set of 4,857 B-ALL patients from three cohorts, we identified a novel group of twent...

Novel two-stage deep learning framework for automated pressure injury classification.

OBJECTIVE: The study aims to develop an artificial intelligence (AI) framework for automatic pressure injury (PI) staging directly from raw clinical images, without requiring manual lesion localisation. By integrating a two-stage deep learning approach-combining object detection and image classification-the proposed system seeks to improve diagnostic accuracy, reduce subjectivity and support consi...

Identification of MHC ligands through allele-guided isolation combined with machine learning for improved MHC assignment using ARDisplay-I.

The isolation of MHC ligands and subsequent analysis by mass spectrometry is considered the gold standard for defining targets for T cell-based immuno...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Advanced neuroimaging for central nervous system infections: when, where, how, and why?

PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mortality worldwide, particularly in children, older ...

CT Radiomic Features Are Associated with DNA Copy Number Alterations of Head and Neck Squamous Cell Carcinomas.

BACKGROUND AND PURPOSE: While a larger fraction of head and neck squamous cell carcinoma (HNSCC) genomes is characterized by a high prevalence of copy...

Machine learning predicts hepatocellular carcinoma risk from routine clinical data: a large population-based multicentric study.

Hepatocellular carcinoma (HCC) is a highly fatal tumor, for which risk stratification is crucial, yet remains challenging. Here, we develop an interpr...

Digitally Assessed Nucleolar Size Compared to Traditional Pathologist WHO Grade Allocation in Clear Cell Renal Cell Carcinoma.

Traditional WHO grading for renal cell carcinoma (RCC), largely based on nucleolar prominence, has well-known intraobserver and interobserver variabil...

Automated acquisition of explainable knowledge from unannotated colposcopic images for predicting the natural course of CIN2.

OBJECTIVE: Cervical intraepithelial neoplasia grade 2 (CIN2) represents a critical turning point in cervical cancer progression. While its natural reg...

Comparison of breast ultrasound image classification accuracy between convolutional neural networks and human experts using multicenter external validation cohort data.

PURPOSE: In recent years, much research has been conducted on ultrasound diagnosis of breast tumors using convolutional neural networks (CNNs). While ...

Contemporary Indications and Technical Limits of Transoral Laser Microsurgery for Laryngeal Squamous Cell Carcinoma.

Transoral laser microsurgery (TOLMS) is an established organ-preserving treatment for early-stage and selected intermediate-stage laryngeal squamous c...

A Deep Learning-Driven Framework Integrating Organoid-Based Functional Validation Identifies Universal Neoantigens from Recurrent Glioma Mutations.

Glioblastoma (GBM) is the most common malignant intracranial tumor in adults, with a median survival of only 16-20 months. Neoantigen therapy has show...

Path forward: Cryoablation for colorectal liver metastases.

PURPOSE: Colorectal liver metastases (CRLM) are a leading cause of mortality in patients with colorectal cancer. While surgical resection is the stand...

Advanced imaging techniques for tumor intraoperative navigation imaging.

Cancer remains a leading cause of mortality and morbidity, with surgical resection being a fundamental element of treatment. However, early detection ...

Tumor vessel phenotype in colorectal cancer microenvironment according to age at diagnosis.

BACKGROUND: Given the global issue of the rising incidence of early-onset colorectal cancer (CRC), we tested the hypothesis that tumor vasculature phe...

In-silico study of machine learning discovers de novo lipogenesis for predicting prognosis and immunotherapy responses in kidney renal clear cell carcinoma.

Whole-body magnetic resonance imaging for cancer screening in asymptomatic adults: a multicenter study.

OBJECTIVES: Whole-body MRI is increasingly used for preventive health screening; however, the prevalence and distribution of incidental oncologically ...

Bone Metastasis Detection at CT with Deep Learning Models Trained Using Multicenter, Multimodal Reference Standards: Development and Evaluation.

Purpose To develop and validate deep learning models for detecting bone metastases on abdominal and thoracic CT scans, considering lesion visibility, ...

Integrating Mechanistic Modeling and Machine Learning to Study CD4+/CD8+ CAR-T Cell Dynamics with Tumor Antigen Regulation.

Chimeric antigen receptor (CAR) T cell therapy has shown remarkable success in hematological malignancies, yet patient responses remain highly variabl...

An interpretable machine learning model combining MRI-DKI habitat radiomic features and clinical biomarkers for noninvasive prediction of lymphatic metastasis in rectal cancer: a prospective study.

OBJECTIVE: Tumor heterogeneity exerts a significant influence on lymphovascular invasion (LVI) and lymph node metastasis (LNM) in rectal cancer (RC), ...