Oncology/Hematology

Integrated Single Cell Spatial Analysis Reveals Dysregulated Basal Progenitor Cells in Ulcerative Colitis Pathogenesis: A Multi Omics Study.

BACKGROUND AND AIMS: Ulcerative colitis (UC), a chronic inflammatory bowel disease, causes persistent mucosal inflammation and epithelial dysfunction. Basal progenitor cells (BPCs), critical for intestinal regeneration and mucosal repair, exhibit altered behavior in UC. Despite extensive research into immune dysregulation, the spatial dynamics and functional roles of BPCs in UC remain poorly under...

Single-inspiratory quantitative CT nomogram for enhanced PRISm and COPD differentiation: a cross-sectional study with interpretable diagnostic boundaries.

BACKGROUND: Differentiating preserved ratio impaired spirometry (PRISm) from chronic obstructive pulmonary disease (COPD) is challenging. Traditional biphasic CT scans are limited by radiation exposure, while single-inspiratory CT-based deep learning lacks interpretability. This study aimed to develop a single-inspiratory quantitative computed tomography (QCT) nomogram integrating parenchymal, air...

Performance across different versions of an artificial intelligence model for screen-reading of mammograms.

OBJECTIVES: Studies have reported promising results regarding artificial intelligence (AI) as a tool for improved mammographic screening interpretive ...

Integration of interpretable multi-features and multi-loss functions for multi-functional therapeutic peptide prediction via dataset construction.

Multi-functional therapeutic peptides (MFTP) play a crucial role in drug development, exhibiting properties such as anti-cancer, anti-inflammatory eff...

Lesion-level prediction of local recurrence after stereotactic radiotherapy for brain metastases using machine learning and mixed-effects modeling.

BACKGROUND: The aim of this study was to identify and validate clinically meaningful predictors of local treatment failure (LTF) after stereotactic ra...

Randomized evidence on AI-enabled personalized treatment planning for adults with depressive-anxiety Spectrum disorders: A systematic review and Meta-analysis.

BACKGROUND: AI-enabled personalized treatment planning may improve outcomes by tailoring care, yet its clinical impact across modalities remains uncer...

NEIL1 suppresses ROS accumulation to promote temozolomide resistance and malignant progression in glioma cells.

BACKGROUND: Glioma is the most common malignant primary brain tumor. Temozolomide (TMZ) is the standard first-line chemotherapy, but its efficacy is s...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological malignancies but faces formidable challenges in s...

CT-free attenuation and scatter correction of [11C]CFT brain PET using a Bi-directional matching network.

Quantitative PET imaging requires accurate attenuation and scatter correction (ASC), but the standard CT-based method introduces additional radiation ...

Cell type composition in bulk prostate cancer tissue is a prognostic biomarker.

Prostate cancer, among the most prevalent cancer types globally, exhibits marked heterogeneity and varying disease progression and clinical outcomes. ...

AI-guided integrative discovery of PD-1/PD-L1 interface inhibitors through multiscale modeling and experimental validation.

The PD-1/PD-L1 protein-protein interaction (PPI) is a critical immune checkpoint, and its inhibition represents a powerful strategy in oncology. Disru...

A research on applying the diffusion model algorithm for Infrared and Raman spectroscopy data augmentation to improve the accuracy of diseases.

In recent years, Raman and Infrared spectroscopy have become important tools in disease diagnosis due to their high sensitivity and non-invasive detec...

Artificial intelligence agents in cancer research and oncology.

Since 2022, artificial intelligence (AI) methods have progressed far beyond their established capabilities of data classification and prediction. Larg...

CTSB-positive tumor-associated macrophages shape prognosis and therapeutic response in lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) remains a major clinical challenge in assessment of clinical outcomes and therapeutic response. Although tumor-...

Shap-interpretable predictive modeling of microvascular invasion and early recurrence in hepatocellular carcinoma using MRI habitat imaging combined with clinical features.

OBJECTIVE: To develop and validate an integrated model combining Gd-EOB-DTPA-enhanced MRI habitat imaging with clinical features for preoperative pred...

C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identi...

Machine learning-guided identification of metastasis-associated miRNAs and their integration into a PFI-based cox risk score and nomogram.

BACKGROUND: Metastasis drives mortality in breast invasive carcinoma. We sought miRNA biomarkers that (i) discriminate metastatic potential, (ii) stra...

Machine learning assisted raman spectroscopy for the classification of ovarian cancer cells.

Ovarian cancer is one of the most lethal gynecological malignancies, asymptomatic early progression, ineffective screening, and high histological hete...

Machine Learning-Based Prediction Model for Delayed Chemotherapy-Induced Nausea and Vomiting in Pediatric Cancer: A Prospective Cohort Study.

BACKGROUND: Delayed chemotherapy-induced nausea and vomiting (CINV) in pediatric oncology patients is currently under-recognized. This study aims to d...

Utilizing artificial intelligence for the diagnosis of ocular surface squamous neoplasia with ultrasound biomicroscopy images.

PURPOSE: This study aims to develop an artificial intelligence (AI) model to assist ophthalmologists in distinguishing ocular surface squamous neoplas...