Oncology/Hematology

Development and validation of a multiple myeloma diagnostic model based on systemic lupus erythematosus-associated genes and identification of specific genes.

BACKGROUND: Monoclonal immunoglobulins are commonly found in multiple myeloma (MM), a prevalent hematologic malignancy that is currently incurable. In recent years, the association between systemic lupus erythematosus (SLE), an autoimmune disease, and MM has garnered increasing attention. However, there remains a lack of in-depth research regarding the interactions between these two conditions and...

Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images.

OBJECTIVES: Lymphovascular invasion significantly impacts the prognosis of urothelial carcinoma of the bladder. Traditional lymphovascular invasion detection methods are time-consuming and costly. This study aims to develop a deep learning-based model to preoperatively predict lymphovascular invasion status in urothelial carcinoma of bladder using CT images.

Machine Learning-based Dose Prediction in [Lu]Lu-PSMA-617 Therapy by Integrating Biomarkers and Radiomic Features from [Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography.

PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorbed doses (ADs) in kidneys and tumoral lesions for ...

The Role of Artificial Intelligence (ChatGPT-4o) in Supporting Tumor Board Decisions.

Artificial intelligence (AI) has emerged as a promising field in the era of personalized oncology due to its potential to save time and workforce whi...

Advancements in Hematologic Malignancy Detection: A Comprehensive Survey of Methodologies and Emerging Trends.

The investigation and diagnosis of hematologic malignancy using blood cell image analysis are major and emerging subjects that lie at the intersection...

Artificial Intelligence Assisted 18F-FDG PET Radiomics in Classifying Histological Subtypes of Lung Cancer: Systematic Review and Meta-analysis.

UNLABELLED: AI-assisted radiomics is an emerging tool for precision oncology, and many studies have recently shown promising results. However, there a...

Hybrid machine learning for real-time prediction of edema trajectory in large middle cerebral artery stroke.

In treating malignant cerebral edema after a large middle cerebral artery stroke, clinicians need quantitative tools for real-time risk assessment. Ex...

MRI-based radiomics for differentiating high-grade from low-grade clear cell renal cell carcinoma: a systematic review and meta-analysis.

PURPOSE: High-grade clear cell renal cell carcinoma (ccRCC) is linked to lower survival rates and more aggressive disease progression. This study aims...

Exploring potential methylation markers for ovarian cancer from cervical scraping samples.

BACKGROUND: Ovarian cancer has the highest mortality rate among gynecological cancers, making early detection crucial, as the five-year survival rate ...

Clinical Validation and Post-Implementation Performance Monitoring of a Neural Network-Assisted Approach for Detecting Chronic Lymphocytic Leukemia Minimal Residual Disease by Flow Cytometry.

: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-o...

Interleukin-6 Is a Crucial Factor in Shaping the Inflammatory Tumor Microenvironment in Ovarian Cancer and Determining Its Hot or Cold Nature with Diagnostic and Prognostic Utilities.

Ovarian cancer (OC) remains the leading cause of cancer-related deaths among women, often diagnosed at advanced stages due to the lack of effective ea...

Artificial Intelligence as a Potential Tool for Predicting Surgical Margin Status in Early Breast Cancer Using Mammographic Specimen Images.

: Breast cancer is the most common malignancy among women globally, with an increasing incidence, particularly in younger populations. Achieving compl...

Machine Learning Based Assessment of Inguinal Lymph Node Metastasis in Patients with Squamous Cell Carcinoma of the Vulva.

: Despite great efforts from both clinical and pathological sides to address the extent of metastatic inguinal lymph node involvement in patients with...

Radiomics of Dynamic Contrast-Enhanced MRI for Predicting Radiation-Induced Hepatic Toxicity After Intensity Modulated Radiotherapy for Hepatocellular Carcinoma: A Machine Learning Predictive Model Based on the SHAP Methodology.

OBJECTIVE: To develop an interpretable machine learning (ML) model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic data,...

Construction of Sonosensitizer-Drug Co-Assembly Based on Deep Learning Method.

Drug co-assemblies have attracted extensive attention due to their advantages of easy preparation, adjustable performance and drug component co-delive...

The integrated single-cell analysis interpret the lactate metabolism-driven immune suppression in triple-negative breast cancer.

BACKGROUND: Individuals with triple-negative breast cancer (TNBC) exhibit elevated lactate levels, which offers a valuable lead for investigating the ...

FDG-PET intensity normalization improves radiomics- based survival prediction in oropharyngeal cancer patients: a comparison of the SUV with alternative normalization techniques.

BACKGROUND AND PURPOSE: Despite the widespread research application of radiomics, there is a knowledge gap regarding the optimal voxel intensity norma...

Gene expression and agent-based modeling improve precision prognosis in breast cancer.

Breast cancer survival is hard to predict because of the complex ways genes and cells interact. This study offers a new method to improve these predic...

Artificial Intelligence and Data Science Methods for Automatic Detection of White Blood Cells in Images.

Data scieQuerynce (DS) methods and artificial intelligence (AI) are critical in today's healthcare services operations. This study focuses on evaluati...

Fibrogenesis-driven tumor progression in clear cell renal cell carcinoma: prognostic, therapeutic implications and the dual role of neuropilin-1.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the predominant subtype of renal cancer, with a poor prognosis driven by therapy resistance and...