Latest AI and machine learning research in hiv/aids for healthcare professionals.
EEG-based subject identification is an emerging biometric approach with strong potential for secure authentication, but reliable performance requires optimisation of the entire processing pipeline. The key difficulty lies in improving signal quality while preserving the subtle neural signatures that uniquely distinguish individuals . In this study, we propose a complete framework that integrates l...
BACKGROUND: Epidermal growth factor (EGF) and its receptor EGF(EGFR) play crucial roles in glioblastoma (GBM) prognosis. However, non-invasive assessment of their expression remains challenging. This study aimed to determine whether radiomics features extracted from contrast-enhanced MRI could predict EGFR expression in high-grade gliomas (HGG) and to explore their associations with immune infiltr...
The use of generative machine learning models, trained on the experimentally resolved structures deposited in the protein data bank, is an attractive ...
Upper-limb prosthesis control remains challenging in achieving natural and intuitive movements, especially for devices with multiple actuated degrees ...
BACKGROUND: Survival outcomes in locally advanced gastric cancer remain heterogeneous despite standard treatment and outcome classifications. Visceral...
High-dimensional data with left-censored responses are increasingly common in modern applications, yet existing methods for analyzing them are limited...
BACKGROUND: Cognitive dysfunction (CD) is a frequent but often underrecognized clinical feature in systemic lupus erythematosus (SLE) patients. It mar...
OBJECTIVE: The lung is commonly involved in advanced Kaposi sarcoma (KS) but diagnosis of pulmonary KS in low-resource settings is difficult. Clinical...
BACKGROUND: Animal anatomy is revolutionised by use of digital techniques where it is implicated in research, education, and diagnostics. Modern compu...
Sustained engagement in HIV care and adherence to ART are crucial for meeting the UNAIDS "95-95-95" targets. Disengagement from care remains a signifi...
AR/VR and other immersive technologies are creating dynamic, learner-centred, and engaging language-learning environments. In these ever-changing situ...
OBJECTIVE: To examine the influence of the emerging use of generative artificial intelligence (GenAI) within electronic health records and among the p...
BACKGROUND: FDG-PET aids presurgical epilepsy evaluation but is limited by access and radiation exposure. PURPOSE: To evaluate synthetic FDG-PET gener...
BACKGROUND: Cardiovascular disease screening faces significant challenges in resource-limited settings, where infrastructure and computational constra...
BACKGROUND: This study aimed to elucidate key molecular alterations in the osteoarthritis (OA) synovial microenvironment through transcriptomic analys...
OBJECTIVES: To improve prediction and understanding of TB dynamics in Argentina, identifying key risk factors and high-incidence areas to inform surve...
BACKGROUND: Sjögren's syndrome (SS) is a chronic autoimmune disorder characterized by significant diagnostic challenges due to nonspecific symptoms an...
The immune defense function protecting the body from invasive pathogens is a key indicator of an individual's health and lacks of methods for quantita...
Viruses are a significant threat to human life, as demonstrated by the global COVID-19 pandemic and the Ebola outbreak. Diseases such as smallpox, AID...
BACKGROUND: Various artificial intelligence-based medical technologies have been used for diagnosing and treating diseases. Although moyamoya disease ...