Oncology/Hematology

Probabilistic cancer risk assessment from heavy metal exposure in iranian rice and pasta: a novel hybrid framework integrating INAA, ICP-AES, and ensemble machine learning.

This study investigates cancer risk from heavy metal exposure in rice and pasta using experimental data and machine learning approaches, based on 19 experimental samples and 1,750 simulated exposure instances. Concentrations of toxic heavy metals were quantitatively measured in multiple rice varieties and pasta types using Instrumental Neutron Activation Analysis (INAA) and ICP-AES analytical tech...

A multi-level attention CNN-transformer based framework for the detection of brain tumor using regional dual-score explainability.

Deep learning models for brain tumor diagnosis often lack interpretability beyond qualitative visual heatmaps. Clinicians require not only tumor localization but also quantitative assessment of explanation quality and diagnostic relevance, capabilities absent in conventional explainability methods. This paper introduces a classification-explainability framework addressing these limitations. The Mu...

Integrating machine learning and structural analysis to decipher benzo[a]pyrene-induced bladder cancer networks.

Benzo[a]pyrene (BaP), a polycyclic aromatic hydrocarbon from tobacco smoke, exhaust, and pollutants, is linked to bladder cancer (BLCA). We systematic...

Immune Checkpoint Inhibitor-Associated Cardiovascular Toxicity: Mechanisms, Clinical Manifestations, and Clinical Impact.

Immune checkpoint inhibitors (ICIs) represent a class of novel anticancer agents that enhance T cell-mediated recognition and elimination of tumor cel...

Bioinformatic and experimental analysis reveals ITGA5 as a driver of ovarian clear cell carcinoma progression and platinum resistance.

UNLABELLED: Ovarian clear cell carcinoma (OCCC) is a clinically aggressive subtype of epithelial ovarian cancer with limited therapeutic options. Here...

Performance of a self-attention-based model in the task of differentiating clear cell renal cell carcinoma from other renal tumors: variable Vision Transformer (vViT).

OBJECTIVES: To examine the performance of the variable Vision Transformer (vViT) in comparison with that of convolutional neural networks (CNNs) in th...

Prognostic Significance of Baseline 18F-FDG PET/CT Parameters in Combination with an Artificial Intelligence-Based Pleural Effusion Segmentation Model for Malignant Pleural Effusion.

OBJECTIVES: We aimed to use an artificial intelligence (AI)-based pleural effusion segmentation model on baseline 18F-FDG positron emission tomography...

Preoperative identification of tumor deposits in rectal cancer using a transformer-based multimodal fusion model: a multicenter retrospective study.

OBJECTIVE: To develop and validate a transformer-based deep learning-radiomics model for the non-invasive preoperative discrimination of tumor deposit...

A hybrid deep learning framework for accurate breast cancer classification using MRI images.

Early and accurate detection of breast cancer is crucial to enhance patient results, especially in high-risk populations where magnetic resonance imag...

Development and validation of an MRI-based deep learning system for triple-class ER expression classification in breast cancer: a large-scale multicenter study.

BACKGROUND: Estrogen receptor (ER) expression is a key prognostic and predictive marker in breast cancer. The 2020 ASCO/CAP guidelines classify tumors...

Single-cell analysis reveals that NRG1/3-ERBB4 signaling affects metabolic reprogramming and immune escape in Wilms tumor.

BACKGROUND: Wilms tumor presents a heterogeneous tumor microenvironment. This study aimed to characterize the tumor microenvironment and identify prog...

Precise Staging of Diabetic Retinopathy Through Machine Learning Analysis of Leakage Source Characteristics: A Radiomics-Driven Approach Integrating OCT-A and FFA.

INTRODUCTION: Evaluating retinal fundus image for diabetic retinopathy (DR) assessment is used to reduce the risk of blindness among diabetic patients...

Mechanism of UBE2T regulating endometrial cancer proliferation through m6A modification.

Endometrial cancer (EC) is a prevalent malignancy in women. UBE2T, a member of the E2 ubiquitin-conjugating enzyme family, has emerged as a potential ...

Machine Learning-Based Prediction of Central Line-Associated Bloodstream Infection in Children with Acute Leukemia.

Central line-associated bloodstream infection (CLABSI) is a frequent and severe complication in children undergoing treatment for acute leukemia, subs...

Artificial intelligence-based vascular pattern profiling predicts prognosis and therapeutic response in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by active angiogenesis and heterogeneous vascular patterns. However, vascular pattern prof...

Development and Validation of a Deep Learning-enabled Single Breath-hold Abbreviated MRI Protocol for Hepatocellular Carcinoma Diagnosis.

Purpose To develop a deep learning-enabled single breath-hold abbreviated MRI (DL-SBH-aMRI) protocol for hepatocellular carcinoma (HCC) diagnosis. Mat...

Tumor-preserving Deformable Registration of Longitudinal Breast DCE MRI during Neoadjuvant Chemotherapy.

Purpose To develop a deep learning-based deformable registration method for breast dynamic contrast-enhanced (DCE) MRI that preserves tumor regions wh...

A hybrid radiomics framework integrating genetic algorithm-optimized random forest for preoperative identification of Luminal B breast cancer and Ki-67 prediction: A multicenter study.

BACKGROUND: Preoperative identification of Luminal B breast cancer remains a clinical challenge. This study aimed to develop an ultrasound radiomics f...

Cytokine-induced killer (CIK) Cells-associated transcriptome signature reveals the potential immunomodulatory role of TNFSF14 in clear cell renal cell carcinoma.

Among adoptive immune cell therapies, cytokine-induced killer cell (CIK) therapy has demonstrated clear therapeutic relevance in multiple cancers, par...

PFAS is associated with perineural invasion in triple-negative breast cancer with a potential role for Cathepsin D dysregulation: a multi-omics and experimental study.

Per- and polyfluoroalkyl substances (PFAS) are persistent pollutants linked to breast cancer (BC), but their role in perineural invasion (PNI) of trip...