Latest AI and machine learning research in surveillance for healthcare professionals.
Respiratory disease outbreaks burden U.S. healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag 1-2 weeks behind real-time conditions, preventing timely intervention. We developed a machine learning early warning system that combines Google search trends with traditional epidemiological data using ensemble voting algorithms to predict the timing o...
Falls among elderly residents in assisted living facilities (ALFs) are prevalent, costly, and frequently under-documented. AUGi, a wall-mounted device employing obfuscated computer vision, deep learning, and mobile integration, provides continuous monitoring while maintaining patient privacy. To evaluate whether the use of AI-assisted detection of falls could improve documentation of falls and lea...
Loneliness is a major psychological challenge in older adulthood, contributing to increased risks of depression, anxiety, and mortality. Conversationa...
Skin neglected tropical diseases (NTDs) such as cutaneous leishmaniasis, lymphatic filariasis, mycetoma, and podoconiosis affect millions in endemic r...
The integration of causal inference, artificial intelligence (AI), and multi-omics data represents a transformative frontier for unravelling the compl...
Simulation models inform health policy decisions by integrating data from multiple sources and forecasting outcomes when there is a lack of comprehens...
Lymphoma diagnosis remains challenging due to diverse subtypes and nonspecific presentations. While prior research focused primarily on clinical accur...
Should original research routinely contain prominent policy claims, such as recommendations for policymakers or broad calls to action? Growing emphasi...
The concept of fairness has been extensively examined within the domains of Machine Learning and Artificial Intelligence more broadly. It remains, how...
Threatened miscarriage represents one of the most prevalent obstetric emergencies globally. Nevertheless, women experiencing first-trimester bleeding ...
The estimates of national disease risk are considerably limited by the time of conducted surveys and the geographical inadequacies in surveillance, no...
Heart failure with preserved ejection fraction (HFpEF) accounts for over half of all heart failure cases in the United States and remains a diagnostic...
Current research on Gender-Based Violence (GBV) typically separates predictive machine learning and causal inference into distinct analytical silos. Y...
Artificial intelligence (AI) models with medical images as input data are increasingly proposed to support clinical decisions in lung cancer screening...
Severe cutaneous adverse reactions (SCARs), including Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS-TEN), drug reaction with eosinophilia a...
This study aimed to systematically review and critically evaluate the risk of bias and applicability of surgical site infection (SSI) risk prediction ...
Vector-borne diseases, including dengue, threaten the health and livelihoods of over 80% of the world's population, particularly in tropical and subtr...
Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic disparities, poor sanitation, and environmental fa...
Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet existing methods often struggle with accuracy and robu...
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting ...