Lymphoma

An artificial intelligence model to detect abnormal ejection fraction from non-contrast chest computed tomography: the CT-LVEF study.

AIMS: Heart failure (HF), a major global health challenge, affects millions worldwide and poses substantial healthcare and economic burdens. It is estimated that a large proportion of those with early systolic dysfunction remain asymptomatic at a stage when guideline-directed medical therapies have been shown to prevent disease progression. To develop an artificial intelligence (AI) model capable ...

Spinal cord FDG PET uptake in healthy adults: an AI-driven segmentation study.

PURPOSE: 18F-fluorodeoxyglucose (FDG) Positron Emission Tomography (PET)/Computerized Tomography (CT) is an important imaging modality in oncology, but its use in spinal cord assessment is limited due to a lack of baseline metabolic reference values. Regional spinal cord FDG uptake, especially in healthy populations, remains poorly defined, limiting accurate delineation between physiological and p...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Computational pathology model to predict recurrence-free survival in NMPUC patients on BCG-therapy.

Urothelial carcinoma, predominantly appearing as non-muscle-invasive papillary urothelial carcinoma (NMIPUC), exhibits wide clinical variability. Accu...

Analysis of vehicle-related non-exhaust PM10 and emerging pollutants in Beijing with machine-learning.

With the growth of electric vehicles, non-exhaust PM10 is becoming the dominant contributor to vehicle-related particulate pollution and a source of e...

A false discovery rate control method using a fully connected hidden Markov random field for neuroimaging data.

False discovery rate (FDR) control methods are essential for voxel-wise multiple testing in neuroimaging data analysis, where hundreds of thousands or...

Beyond 0.29±0.02 mm intrinsic spatial resolution based on monolithic crystals using convolutional neural network: a simulation study.

High spatial resolution is important for a Positron Emission Tomography (PET) system. Monolithic crystal based detectors are promising to deliver ...

Predicting 5-Year Mortality in Non-Small-Cell Lung Cancer Using the Korean Central Cancer Registry: Model Development and Validation Study.

BACKGROUND: Non-small-cell lung cancer (NSCLC) is one of the most common cancers and a leading cause of cancer-related mortality, making prognostic pr...

Integrative single-cell and spatial transcriptomics analysis reveals a baicalein-responsive 10-gene signature for non-small cell lung cancer.

BACKGROUND: Non‑small cell lung cancer (NSCLC) remains a leading cause of cancer‑related mortality worldwide. Baicalein, a natural flavonoid, has show...

Integrated CT-PET radiogenomics and graph-based multi-task learning for preoperative prediction of key glioma molecular markers.

BACKGROUND: The clinical management of glioma is increasingly dependent on the tumor's molecular profile, particularly the mutation status of Isocitra...

Ultrasound-based multiregional radiomics nomogram for predicting recurrence in HER2-positive breast cancer.

PURPOSE: Accurate prediction of recurrence risk is crucial for personalizing therapy in human epidermal growth factor receptor 2-positive (HER2-positi...

Effects of cerebral infarction on cognitive and speech performance.

OBJECTIVE: The present study sought to identify the cognitive features and speech features that might distinguish cerebral infarction patients by usin...

A novel deep learning network for small bowel ulcerative lesion detection and differential diagnosis on double-balloon endoscopy images.

Differentiating small bowel ulcerative diseases (SBUDs) on double-balloon endoscopy (DBE) is challenging. We aimed to develop an artificial intelligen...

Multiobjective optimization of natural convection and entropy generation in a porous wavy cavity with a heated star-shaped obstacle using a hybrid nanofluid.

Convectional heat transfer continues to receive extensive research attention due to its importance in vital applications such as solar energy collecto...

Imaging foundation model for universal enhancement of non-ideal measurement CT.

Non-ideal measurement computed tomography (CT) employs suboptimal imaging protocols to expand CT applications. However, the resulting trade-offs degra...

GPDM: generation-prior diffusion model for accelerated direct attenuation and scatter correction of whole-body 18F-FDG PET.

Accurate attenuation and scatter correction is essential in positron emission tomography (PET) for reliable visual interpretation and quantitative ana...

Machine learning-driven prediction of mechanical properties of lightweight concrete based on experimental data.

Lightweight concrete (LWC) is increasingly used in structural and non-structural applications due to its ability to reduce self-weight while maintaini...

Prospective germline exome and machine learning-based risk score identify predictive and prognostic biomarkers of immunotherapy outcomes in advanced non-small cell lung cancer.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). However, a su...

The relationship between AI self-efficacy and critical thinking among nursing students: A network analysis.

AIM: This study used network analysis to characterize the internal structure of artificial intelligence self-efficacy (AISE) among nursing students an...

Obstruction-Mediated Breakup of Shear-Thinning Droplets in Microfluidic Environment: Experiments, Simulations, and ANN Insights.

We report the breakup dynamics of shear-thinning droplets in microfluidic environment through a comprehensive integration of experiments, numerical si...