Latest AI and machine learning research in devices and vaccines for healthcare professionals.
Antibodies targeting small molecules play indispensable roles in food safety, environmental monitoring, clinical diagnostics, and immunotherapy. The generation of such antibodies critically depends on hapten design. Although several generic antibody databases exist, an open resource that specifically integrates haptens and the corresponding antibody performance has remained unavailable, thereby li...
Somalia's fragile health system, strained by decades of conflict, climate shocks, and persistently low immunization coverage, remains dangerously vulnerable to preventable disease outbreaks. With measles resurgent and full vaccination coverage stagnating at just 55% nationally and as low as 26% in some states - the country faces recurrent epidemics it cannot withstand. Digitalization and artificia...
Machine learning (ML) models integrating genetic and clinical data show promise for personalizing antiplatelet therapy after myocardial infarction (MI...
BACKGROUND: Frailty remains a significant risk factor for adverse health outcomes in hospitalized patients. Few have evaluated frailty risk and its in...
CONTEXT: Running is good for overall health but has a poorly understood risk of injury. Wearable technology and machine learning (ML) offer solutions ...
BACKGROUND: Chagas disease (ChD), a neglected cardiovascular condition, affects 7.5 to 10.5 million people worldwide. Opportunistic screening during r...
INTRODUCTION: Endovascular thrombectomy (EVT) is the standard of care for large vessel occlusion stroke, but the optimal first-line strategy remains d...
OBJECTIVE: Traumatic cardiac arrest differs from non-traumatic regarding epidemiology. This study evaluated five machine learning classifiers' ability...
BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...
BACKGROUND AND AIM: Pharmacovigilance is essential to ensuring patient safety by enabling timely identification of adverse reactions in increasingly c...
BACKGROUND: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinica...
BACKGROUND: Adverse drug events (ADEs) pose significant public health challenges and economic burdens. While substantial ADE information is documented...
In periodontology, Artificial Intelligence (AI) applications, ranging from radiographic evaluation to outcome prediction, are emerging. However, their...
OBJECTIVES: The aim of the present study was therefore to evaluate whether a programmed artificial intelligence (AI) system can reliably differentiate...
The integration of optical sensing with neuromorphic computing offers a promising pathway to overcome the von Neumann bottleneck in data-intensive art...
This mixed-methods study assessed whether reasoning-enabled large language models (LLMs) can classify stances towards COVID-19 vaccination on X (forme...
OBJECTIVE: Abdominal ultrasound is widely used for the routine screening of hepatobiliary and renal diseases because it is safe, inexpensive and broad...
BACKGROUND: Precision periodontology integrates molecular diagnostics, genomics, and advanced imaging into clinical decision-making. Despite major adv...
This study aimed to develop and validate a multimodal prediction model integrating biomechanical and radiological variables to predict internal fixati...
PURPOSE: To describe a new clinical protocol for prosthetically guided implant placement with the assistance of a robotic system. MATERIALS AND METHOD...