Nuclear medicine has become an indispensable discipline in the diagnosis and
management of musculoskeletal infections. Radionuclide tests serve as a valuable …

Abstract» Nuclear imaging techniques, including bone scintigraphy, labeled leukocyte
scintigraphy, positron emission tomography (PET), and single-photon emission computed …

Purpose This study assesses the reliability of deep learning models based on planar whole-
body bone scintigraphy for diagnosing Skull base invasion (SBI) in nasopharyngeal …

Background To evaluate the clinical performance of two deep learning methods, one
utilizing real clinical pairs and the other utilizing simulated datasets, in enhancing image …

Abstract Purpose To predict Gleason Score (GS) using radiomic features from 68Ga-PSMA-
PET/CT images in primary prostate cancer. Methods 138 patients undergoing 68Ga-PSMA …

Propose An electrocardiogram (ECG) has been extensively used to detect rhythm
disturbances. We sought to determine the accuracy of different machine learning in …

Myocarditis, characterized by inflammation of the myocardial tissue, presents substantial
risks to cardiovascular functionality, potentially precipitating critical outcomes including heart …

Results In the head and neck, chest, chest-abdomen interval, abdomen, and pelvis regions,
the best models achieved area under the curve, accuracy, sensitivity, and specificity of [0.97 …

Artificial intelligence (AI) is emerging in various domains of our life [1]. In the medical
domain, great promises are attributed to this technology to empower the field of medical …

The objective of this study is to assess the efficacy of advanced augmentation techniques,
such as stable diffusion, in improving the performance of deep learning models in the …