OBJECTIVES: Current study aimed to investigate radiomics features derived from 2-centre diffusion-MRI to differentiate benign and hepatocellular carcinoma (HCC) liver nodules.
The aim of this research is to help health care professionals to automatically detect lower urinary tract disorders using sounds of voiding recorded at home. In total 93 patients were diagnosed as obstructed or non-obstructed in a hospital using trad...
Pathological tremor significantly impairs daily activities and quality of life, particularly in conditions such as essential tremor and Parkinson's disease. The assessment and evaluation of tremor, along with its evolution with medication dosages, po...
OBJECTIVE: We aimed to develop a machine learning (ML) model to preoperatively predict surgical difficulty for pheochromocytomas and paragangliomas (PPGLs) using clinical and radiomic features.
OBJECTIVES: To investigate the predictability of late cervical lymph node metastasis using radiomics analysis of ultrasonographic images of tongue cancer.
A novel data enhancement method for olfactory visual images was proposed in this study, combined with deep learning to achieve the accurate prediction of total volatile basic nitrogen (TVB-N) content in chilled mutton. Specifically, the sliding-windo...
Biomedical physics & engineering express
Jun 13, 2025
: Effective lung gas exchange relies on the balance between alveolar ventilation and perfusion, which can be disrupted in mechanically ventilated patients. Lung perfusion assessment using electrical impedance tomography (EIT) typically involves a sud...
. Understanding speech in the presence of background noise such as other speech streams is a difficult problem for people with hearing impairment, and in particular for users of cochlear implants (CIs). To improve their listening experience, auditory...
International journal of pharmaceutics
Jun 10, 2025
Sticking can significantly affect drug product quality, manufacturing efficiency, and therapeutic efficacy in pharmaceutical tablet manufacturing. This study presents a novel integrated model with a convolutional neural network (CNN) and gray-level c...
Despite decades of advancements in diagnostic MRI, 30%-50% of temporal lobe epilepsy (TLE) patients remain categorized as 'non-lesional' (i.e. MRI negative) based on visual assessment by human experts. MRI-negative patients face diagnostic uncertaint...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.