Oncology/Hematology

Intelligent ensemble learning-enhanced finite element modeling for precision thermal ablation in cancer therapy.

BACKGROUND: Microwave ablation (MWA) is a minimally invasive treatment for liver tumors, yet accurate prediction of ablation zones remains challenging due to tissue heterogeneity, uncertain antenna placement, and complex thermal dynamics. OBJECTIVE: This study develops a hybrid computational framework that integrates finite element modeling (FEM) with supervised machine learning to improve the pre...

Targeted inhibition of colorectal cancer by nano-dihydroartemisinin liposomes: Insights into the disruption of ABCG2 and BCL2 leading to induction of oxidative stress and metabolic disorder.

PURPOSE: Colorectal cancer is an aggressive malignancy characterized by significant drug resistance and a complex tumor microenvironment. Nano-dihydroartemisinin liposomes demonstrate significant potential in inhibiting tumor growth and survival by targeting critical regulatory proteins involved in drug efflux and apoptosis. This study aims to investigate the mechanisms through which nano-dihydroa...

Deep learning for automatic detection of hepatocellular carcinoma in dynamic contrast-enhanced MRI.

OBJECTIVE: Develop a deep learning model for automatic hepatocellular carcinoma (HCC) detection in T1 weighted imaging (WI) Dynamic Contrast-Enhanced ...

18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients.

OBJECTIVE: The aim of this study was to investigate the diagnostic performance of the 2.5-dimensional (2.5D) ensemble deep learning (DL) model based o...

Evaluating the Performance of Claude 3.7 Sonnet in Data Extraction Automation for Systematic Literature Reviews.

OBJECTIVES: To evaluate the performance of Claude 3.7 Sonnet in automating data extraction for systematic literature reviews (SLRs). METHODS: An artif...

Machine Learning-Based Risk Prediction for Feline Mammary Tumours: A Comprehensive Epidemiological Analysis Using Multi-Model Ensemble Approach.

Feline mammary tumours represent the third most common malignancy in cats, with limited evidence-based tools available for risk assessment and screeni...

Artificial intelligence-powered signal analysis of loop-mediated isothermal amplification (LAMP) for the screening of Kaposi sarcoma at the point of care.

Unlike the polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP) lacks a consistent thermal cycle, making quantification part...

Preoperative prediction of cervical cancer recurrence using explainable MRI radiomics: a SHAP-Guided machine learning study.

PURPOSE: To develop and validate a machine learning model that integrated MRI radiomics features and clinical factors for preoperative prediction of p...

Noninvasive follicular thyroid neoplasm with papillary-like nuclear features: an update.

PURPOSE OF REVIEW: Noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) has been recognized as a diagnostic entity sin...

Resting-state functional connectivity of the fronto-limbic and default mode network as neural correlates of antidepressant response in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet antidepressant response remains highly variable, with many...

Automatic segmentation and CT-based deep learning radiomics nomogram for predicting overall survival in patients with small cell lung cancer: A multicenter cohort study.

BACKGROUND AND OBJECTIVE: Accurate prediction of overall survival (OS) in patients with small cell lung cancer (SCLC) is crucial for personalized trea...

Pathologic assessment of resected stage III non-small cell lung cancer after neoadjuvant chemotherapy: identification of additional prognostic factors.

BACKGROUND: Non-small cell lung cancer (NSCLC) patients undergoing neoadjuvant chemotherapy (NACT) followed by surgery represent an ideal clinical set...

The Impact of Radiation Dose to Bowel on the Risk of Developing Gastrointestinal Toxicities When Treating Abdominopelvic Soft-Tissue Sarcomas With Preoperative Radiation Therapy.

PURPOSE: Abdominopelvic soft-tissue sarcomas (AP-STS) are selectively treated with radiation therapy (RT) followed by surgery. We investigated dosimet...

Ensemble Learning Model: A Novel Technique to Detect Malignancy in Effusion Cytology.

AIMS AND OBJECTIVES: This study applied an ensemble learning model combining six transfer learning architectures to detect malignancy in effusion cyto...

Advancing oral leukoplakia progression recognition: A benchmark with dataset, method, and application.

Oral leukoplakia, a potentially malignant disorder, is a critical precursor to oral squamous cell carcinoma (OSCC), which accounts for 90 % of oral ca...

Polyp image segmentation based on parallel dilated convolution and dual attention mechanisms.

Colorectal cancer is usually caused by malignant transformation of early colon polyps. Early polyps are benign, but if left untreated, they can progre...

KLF7 as a biomarker for the pre-metastatic state promotes colorectal cancer liver metastasis via TGFβ autocrine signaling.

Although metastasis-initiating cells drive metastasis, only a certain subpopulation of these cells can successfully disseminate from the primary tumor...

Flavonoid-modulated JAK-STAT signaling mitigates malignant transformation and drug resistance in breast tumors: A clinically relevant 3PM-guided innovation.

BACKGROUND: Breast cancer (BC) treatment efficacy is often compromised by tumor cell plasticity and multidrug resistance of multi-factorial origin. Am...

Integrative Machine Learning Model Leveraging DCE-MRI and PSA Values for Advanced Risk Stratification in Prostate Cancer.

PURPOSE: Accurate grading of prostate cancer is critical for treatment strategies and risk stratification. This study aims to develop a machine learni...

Renal Cell Carcinoma subtyping: Learning from multi-resolution localization.

BACKGROUND AND OBJECTIVE: Renal Cell Carcinoma (RCC) is often diagnosed at advanced stages, limiting treatment options. Since prognosis depends on tum...