Oncology/Hematology

A machine learning model for accurate prediction of CMV end-organ disease.

BACKGROUND: Cytomegalovirus (CMV) End-Organ Disease (EOD) remains a significant complication in immunocompromised individuals, particularly transplant recipients and patients undergoing chemotherapy. Accurate prediction of CMV EOD is essential for timely intervention but remains challenging using traditional methods. OBJECTIVE: This study aimed to evaluate the diagnostic performance of machine lea...

Multi-structure CT radiomics-based consensus model for the diagnosis of pancreatic ductal adenocarcinoma and vascular involvement.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy, with accurate preoperative assessment of vascular involvement critical for determining resectability and treatment planning. Conventional contrast-enhanced CT relies on qualitative evaluations, leading to interobserver variability and diagnostic uncertainty. Existing radiomics studies for PDAC mostly focus on single...

Periodontal bone loss analysis via keypoint detection with heuristic post-processing.

OBJECTIVES: This study proposes a deep learning framework and an annotation methodology for the automatic detection of periodontal bone loss landmarks...

Enhancing therapeutic outcomes with artificial intelligence for HR-positive, HER2-negative metastatic breast cancer.

Cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) are an integral first-line treatment for hormone receptor-positive metastatic breast cancer, though r...

Deep Learning Reconstruction Combined with Contrast-Enhancement Boost Technique in "Quadruple-low" CCTA Protocol: Evaluation of Image Quality and Diagnostic Accuracy.

RATIONALE AND OBJECTIVES: To evaluate the impact of a deep learning reconstruction (DLR) algorithm combined with contrast-enhancement boost (CE-boost)...

Coronary revascularization: a long-term perspective.

This paper will forecast advancements in coronary revascularization by 2040, drawing on historical trends and recent breakthroughs. Having forecasted ...

Randomized controlled trials in valvular heart disease: the evolving role of multimodality imaging.

Valvular heart disease represents a significant global health burden, with an estimated prevalence of 2.5% in high-income countries and projected incr...

NIAID Biodosimetry Strategic Plan.

In the face of emerging threats from natural disasters, nuclear accidents, and potential malicious use of radiation, the National Institute of Allergy...

Deep Learning Identification of Clear Cell Renal Cell Carcinoma on MR Imaging.

OBJECTIVE: To investigate the performance of various convolutional neural networks (CNNs) in identifying clear renal cell carcinoma (ccRCC) on MRI and...

Data-Driven Deciphering Structure-Mössbauer Spectroscopy Relationships in Iron-Based Compounds.

Accurate identification of material structures is crucial for establishing reliable structure-property relationships, yet this task is often hindered ...

Redefining Tumor Vascular Permeability through Deep Learning-Guided Microneedle Delivery.

Low-permeability (LP) tumor vasculature constitutes a major barrier to efficient nanomedicine delivery, making quantitative assessment and mechanistic...

Integrative analysis of immune and microbial subtypes predicts immunotherapy response in stomach adenocarcinoma.

The tumor immune microenvironment and intratumoral microbiota play critical roles in cancer progression and immunotherapy response, yet their integrat...

Transcriptomic subgroups in soft tissue tumors correlate with morphologic subtype, genomic features, and outcome.

PURPOSE: Soft tissue tumors (STT) are highly heterogeneous neoplasms with more than 100 recognized subtypes, many of which lack reliable diagnostic or...

[Imaging of eosinophilic pneumonia : Differential diagnosis in radiological practice].

CLINICAL/METHODICAL ISSUE: Eosinophilic pneumonias are rare inflammatory lung diseases with heterogeneous clinical presentation and variable computer ...

Exploring the toxicological impact of N-nitrosodimethylamine (NDMA) exposure on bladder urothelial carcinoma (BLCA) through network toxicology, machine learning, and multi-dimensional bioinformatics analysis.

BACKGROUND: N-Nitrosodimethylamine (NDMA), classified as a Group 1 carcinogen by the International Agency for Research on Cancer (IARC), is ubiquitous...

Precision imaging and evolving therapies in paragangliomas and pheochromocytomas: from molecular diagnostics to imaging-guided management.

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors originating from neural crest-derived chromaffin tissue, marked by clinica...

Primary tumor-derived, multiparametric MRI-based deep learning-radiomics-clinical model for predicting lymph node metastasis in early-stage cervical cancer.

OBJECTIVES: To develop and validate a primary tumor-derived, multiparametric MRI-based deep learning-radiomics-clinical (DLRC) model for predicting pe...

Spectral CT imaging in colorectal cancer: current applications, limitations, and future perspectives.

Colorectal cancer (CRC) is the third most common malignancy worldwide, and early detection is vital to prevent metastasis and postoperative recurrence...

Radiomics for the Prediction of Postoperative Chronic Kidney Disease in Renal Tumor Patients undergoing Surgical Resection.

OBJECTIVE: Chronic kidney disease (CKD) is a significant concern following renal tumor surgery, impacting long-term renal function and patient outcome...

Clinical Impact of Artificial Intelligence-Augmented Lymph Node Evaluation in Metastatic Gastric, Colorectal, and Breast Cancer.

CONTEXT.—: Lymph node (LN) assessment plays a critical role in cancer staging and prognosis but remains a time-consuming and labor-intensive task in p...