Latest AI and machine learning research in bioterrorism for healthcare professionals.
Accurate interpretation of chest X-rays is a critical clinical skill, yet radiology training in medical education remains limited and often fails to provide broad exposure to a wide variety of conditions, including those that are rare, subtle, or easily confused with one another. Although artificial intelligence (AI) has shown impressive performance in medical image classification, its potential t...
PURPOSE: Surveillance of arboviral vectors and screening for probable infection is very important for the planning of vector control programs, especially in countries where these activities are just beginning. In the present study, we conducted mosquito surveillance at 26 locations predicted to be at risk (according to our recently published study using Machine learning) in the Marrakech-Safi regi...
BACKGROUND: Deficiencies in knowledge and skills related to the management of medical emergencies in dental settings can adversely affect the clinical...
BACKGROUND: The use of large language models (LLMs)-powered chatbots has reshaped how people seek information and advice, including for emotional and ...
Immunotherapy has revolutionized cancer treatment, yet substantial inter-patient response heterogeneity limits therapeutic benefit to specific patient...
BackgroundAsynchronous telemedicine may support home-based pediatric palliative care (PPC) by improving access to professional guidance and reducing c...
High-throughput preclinical perturbation screens, where the effects of genetic, chemical, or environmental perturbations are systematically tested on ...
BACKGROUND: Heart failure with ischemic cause is associated with substantial cardiovascular mortality. SGLT2 (sodium glucose cotransporter 2) inhibito...
SUMMARYAfrica's ongoing struggles with emerging epidemics and antimicrobial resistance (AMR) underscore the urgency of integrating pathogen genomics a...
OBJECTIVE: To develop a high-accuracy prediction model using hybrid machine learning (ML) and explainable artificial intelligence (XAI) techniques for...
BACKGROUND: Body donor dissection is fundamental to medical education but often induces anxiety and emotional distress in students, potentially impact...
INTRODUCTION: To develop and externally validate machine learning (ML) models for predicting treatment response and adverse events in children with at...
BACKGROUND: The epigenetic control of immune responses plays a crucial role in the development and progression of cancer. The need to identify biomark...
BACKGROUND: Nontyphoidal Salmonella enterica (NTS) is a major public‑health threat in the United States of America (U.S.). Evaluating associations bet...
BACKGROUND: Lung adenocarcinoma (LUAD) is a prevalent and lethal malignancy. The three-dimensional (3D) chromatin architecture significantly influence...
Organoids have become mainstay tools for drug discovery and personalized medicine. High-throughput imaging readouts for drug screening of tumor organo...
BACKGROUND: Neoadjuvant treatment response in rectal cancer is highly heterogeneous, complicating patient selection for organ-preservation strategies....
BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare practice and education, requiring students to adapt to technology-supporte...
Histopathology is the cornerstone of oncology diagnosis, while whole-slide images (WSIs) enable the transition to digital, quantitative pathology. Lev...
Emerging and re-emerging infectious diseases (EIDs) represent an escalating threat to global public health, as exemplified by outbreaks of COVID-19, E...