Lymphoma

Deep-learning based image reconstruction enables reduced dose CT pulmonary angiography with non-inferior image quality.

To investigate whether a CT pulmonary angiography (CTPA) protocol with reduced radiation dose and deep-learning based image reconstruction (DLIR) is non-inferior in image quality to standard-dose CTPA using iterative reconstruction. A phantom study was conducted to estimate the additional radiation dose reduction enabled by high-strength deep learning-based image reconstruction (DLIR-H) compared t...

Comparing supervised machine learning and large language models in title-abstract screening.

BACKGROUND: Systematic reviews require reviewers to decide on the eligibility of large numbers of articles derived from database searches. To accelerate review conduct while continuously more literature gets published, past studies proposed automating the title/abstract-screening step by either supervised machine learning or large language models. Because prior studies mainly compared results with...

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...

Explainable AI reveals squamous histology and U-shaped PD-L1 patterns as primary subgroup predictors of neoadjuvant and perioperative immunotherapy benefit in NSCLC: a machine learning analysis.

BACKGROUND: The introduction of neoadjuvant and perioperative immunotherapy has broadened treatment options for resectable non-small cell lung cancer ...

AI-Assisted Medical Documentation in a Multilingual Swiss Health Care System: Proof-of-Concept Study.

BACKGROUND: Medical documentation imposes a significant administrative burden on physicians and reduces time for direct patient care. Artificial intel...

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...

A Foundation Model Based CT Biomarker for Non-Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non-Small Cell Lung Cancer.

Predicting pathological complete response (pCR) to neoadjuvant immunochemotherapy in non-small cell lung cancer (NSCLC) is clinically important yet re...

[A nomogram combining ultrasound radiomics and clinical features for predicting pathological invasiveness of papillary thyroid carcinoma].

OBJECTIVES: To develop a nomogram model combining ultrasound radiomics and clinical features and to evaluate its predictive value for pathological inv...