Lymphoma

Updates on tuberculosis imaging.

Tuberculosis (TB) remains a leading infectious cause of morbidity and mortality worldwide, and major diagnostic and therapeutic challenges persist despite advances in microbiologic and molecular testing. Over the past decade, molecular imaging, especially with FDG PET/CT, has transformed our understanding of TB pathogenesis, the spectrum of early and subclinical disease, mechanisms of disseminatio...

Neural network architectures and normalization techniques for automated sleep stage classification using rodent EEG and EMG signals.

Accurate sleep stage classification in animal models is crucial for translational sleep research, enabling the study of mechanistic pathways and therapeutic interventions. Because manual scoring is labor-intensive and variable, artificial neural networks are increasingly used for automation. However, few models are tailored for animal sleep staging, and direct cross-model comparisons under consist...

Biomarkers of mitochondrial dynamics in idiopathic pulmonary fibrosis: Identification and validation through transcriptomic and single-cell analyses.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease that has increasingly been associated with dysregulated mitocho...

Image Quality and Diagnostic Performance of Accelerated T2-weighted Imaging of Prostate with Deep Learning Reconstruction: A Comparative Study.

PURPOSE: To compare accelerated T2-weighted turbo spin-echo imaging with deep learning reconstruction (DLR-TSE) with conventional T2-weighted TSE (con...

Predicting amyotrophic lateral sclerosis stage based on multi-parameter ultrasound: development and validation of an interpretable machine learning model.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) lacks sensitive, objective staging tools to guide clinical management and trials. Existing methods hav...

Bayesian-regularized neural network analysis of heat and mass transmission in CMC and water hybrid nanofluid with local thermal non equilibrium conditions.

The influences of Marangoni convection and local thermal non-equilibrium effects on CuO-TiO₂/CMC (Carboxymethyl Cellulose)-Water based hybrid nanoflui...

High-resolution deep learning DIXON MRI of the sacroiliac joints is non-inferior to standard MRI in patients with suspected axial Spondyloarthritis.

OBJECTIVE: To compare the standard multi-sequence MRI protocol (sMRI) of the sacroiliac joints with a single high-resolution deep learning-reconstruct...

An AI Based Screening Tool for Detection of Cerebral Venous Thrombosis on Non-Contrast Brain CT.

While non-contrast computed tomography (NCCT) is the primary ‎imaging modality in emergency settings, it has a low sensitivity for detection of ‎Cereb...

Impact of land use on bus driver inattentiveness: Insight into crash risks.

OBJECTIVE: This study examines how roadside land-uses, namely commercial, residential, educational, and recreational establishments located on a typic...

Near-Real-Time Multi-Parametric Quantitative MRI using Parallel Non-Cartesian 6D Spatial-Temporal Dictionary Learning Neural Networks.

OBJECTIVE: Multi-parametric quantitative MRI (qMRI) enables precise targeting during image-guided interventions such as deep brain stimulation. To add...

Ultrafast Infant Brain Quantitative MRI Using Overlapping-Echo Acquisition with Volumetric Physical Simulation of Slice-level Non-Idealities.

OBJECTIVE: Quantitative MRI (qMRI) is sensitive to brain microstructural and metabolic changes; however, existing techniques often unsuitable for asse...

Cell shapes decode molecular phenotypes in image-based spatial proteomics.

Cellular and tissue structures arise from a few cell shapes, which undergo transformations based on biophysical constraints. Despite links between sig...

Clinician-deployable deep hypergraph model integrating clinical and CT radiomics predicts immunotherapy outcomes in NSCLC.

Current image-based deep learning models that predict the benefits of immunotherapy in non-small cell lung cancer (NSCLC) require high-performance har...

CDR-Net: A computerized framework to detect Alzheimer's diseases and mild cognitive impairment.

Alzheimer's disease (AD) and mild cognitive impairment (MCI) are two dementia-related brain illnesses that are prevalent among elders in the twenty-fi...

Clinical Machine Learning Model for Predicting Pathological Complete Response in Patients with Esophageal and Gastroesophageal Junction Adenocarcinoma After Trimodality Therapy.

BACKGROUND: Accurate prediction of pathological complete response (pCR) after preoperative chemoradiation therapy, followed by surgery (trimodality th...

Mammography-based artificial intelligence model for predicting axillary lymph node status after neoadjuvant therapy in breast cancer.

OBJECTIVES: Our objective is to develop a deep learning-based artificial intelligence (AI) model capable of analyzing digital mammography (DM) images ...

Risk prediction model of survival in patients with low-grade serous ovarian cancer: a multicenter Cohort study.

PURPOSE: Accurate prognostic prediction remains a significant challenge in the management of low-grade serous ovarian cancer (LGSOC), a rare and molec...

Predicting CSR authenticity in healthcare organizations: an integrated SEM-IPMA-ANN approach through the lens of self-compassion theory.

PURPOSE: As healthcare business organizations face mounting pressure from civil society to act responsibly, they are expanding and strategically restr...

Clustering by patients-related characteristics identifies specific phenotypes with different prognosis after resection of non-small cell lung cancer: a French nationwide study from the Epithor database.

INTRODUCTION: Lung cancer remains the leading cause of cancer mortality worldwide despite advances in treatment. Patient-related factors beyond tumour...

Machine learning forecasting of electroosmotic MHD flow of a buoyancy-driven ternary nanofluid in converging and diverging channels.

Artificial neural networks (ANNs) are utilized to study the buoyancy-driven electroosmotic flow conveying Blood, Gold (Au), Copper (Cu), and Multi-Wal...