Latest AI and machine learning research in surveillance for healthcare professionals.
The evaluation of fairness in machine learning systems has become a central concern in high-stakes a...
This study evaluates the feasibility of implementing artificial intelligence (AI)-driven disease sur...
Physical adversarial attacks are increasingly studied in settings that resemble deployed surveillanc...
We present the Surveillance Forgery Image Test Range (SurFITR), a dataset for surveillance-style ima...
Extracting vehicle information from surveillance images is essential for intelligent transportation ...
During the COVID-19 pandemic, reported incidence data played a central role in public health surveil...
Background: Secure text messages (TMs) exchanged among interdisciplinary care teams in nursing homes...
Background: The integration of artificial intelligence (AI) into clinical practice holds transformat...
Background. Climate change is intensifying extreme weather events (EWEs) with potentially profound c...
The rapid advancement of AI research automation systems--including AI Scientist, data-to-paper, and ...
Background: Early breast cancer detection remains central to improving clinical outcomes, yet conven...
Background: The FDA Adverse Event Reporting System (FAERS) is a critical pillar of post-marketing ph...
Image restoration, the recovery of clean images from degraded measurements, has applications in vari...
Digital health technologies, including machine learning (ML), are transforming infectious disease ma...
Background Chronic subdural hematoma (cSDH) recurrence requiring reoperation occurs in 5-33% of case...
Physics-informed neural networks (PINNs) are increasingly used in mathematical epidemiology to bridg...
Effective public health planning and intervention strategies necessitate an understanding of the tem...
Despite decades of work, surveillance still struggles to find specific targets across long, multi-ca...
Wastewater-based epidemiology provides a scalable, noninvasive framework for population-level infect...
Background: Multiple stakeholders need to locate results of registered clinical trials but frequentl...
Vision-Language Models (VLMs) offer significant potential in computational pathology by enabling int...