Latest AI and machine learning research in nuclear medicine for healthcare professionals.
BACKGROUND: Improving the image quality of cardiac gating myocardial perfusion single-photon emission computed tomography (CG MP-SPECT) is crucial for accurate diagnosis. Diffusion model (DM) has recently shown promise in MP-SPECT image denoising, but traditional DM typically require extensive computational resources and prolonged processing times. The study aims to develop and evaluate a lightwei...
In Lennox-Gastaut Syndrome (LGS), a severe developmental and epileptic encephalopathy, the absence of validated biomarkers limits our ability to detect disease early, predict outcomes, and guide treatment strategies. This review synthesizes advances in biomarker research spanning electrophysiological, genetic, neuroimaging, and neuroinflammatory domains. Interictal electroencephalography (EEG) pat...
BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure. PURPOSE: To evaluate synthetic FDG-PET gener...
OBJECTIVES: Given the heterogeneous nature of Alzheimer's Disease (AD) and its higher prevalence in females, it is crucial to understand sex-related d...
BACKGROUND: Prostate cancer is the second most common cancer in men, with rising mortality rates necessitating precise risk stratification. High-invas...
RATIONALE AND OBJECTIVES: PD-L1 expression is a critical biomarker in guiding immunotherapy for gastric cancer (GC). This study aims to investigate th...
Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the pot...
OBJECTIVES: This study aims to develop a deep learning model to assist physicians in accurately classifying negative, equivocal, and positive β-amyloi...
The incorporation of a trifluoromethyl (-CF3) group into organic frameworks profoundly influences their physicochemical and biological properties, mak...
The application of machine learning (ML) and artificial intelligence (AI) algorithms in medical imaging is an emerging area of interest, particularly ...
Positron Emission Tomography (PET) is important for breast cancer diagnosis and monitoring, but high costs restrict access. Dual-panel scanners can re...
Positron emission tomography (PET)/computed tomography (CT) for myocardial perfusion imaging (MPI) provides multiple imaging biomarkers, often evaluat...
Quality assessment of crude palm oil remains a critical challenge globally, particularly in resource-poor areas where traditional methods are time-con...
Quantitative PET imaging requires accurate attenuation and scatter correction (ASC), but the standard CT-based method introduces additional radiation ...
OBJECTIVE: To identify pre-treatment determinants of hypothyroidism and decision regret (DR) following radioiodine (RAI) therapy in Graves' disease (G...
PURPOSE: This study aims to develop and validate an interpretable machine learning model that integrates clinical data, radiomics, and deep learning (...
PURPOSE: There has been significant progress in detecting Alzheimer's disease (AD) using retinal imaging. We developed an ensemble learning-based deep...
OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its u...
Assessing small-molecule blood-brain barrier permeability is laborious, yet critical in drug development. Quantitative prediction models are hindered ...
PURPOSE: This study aimed to develop deep learning (DL) models for CT-free attenuation correction and Monte Carlo-based scatter correction in 99mTc-ma...