Latest AI and machine learning research in surveillance for healthcare professionals.
Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was difficult. The primary aim of this study was to assess the changes in compliance with NPIs in healthcare settings using Artificial intelligence (AI) and examine the barriers and facilitators of using AI systems in healthcare. Methods A pre-post-interventio...
Political bias is an inescapable characteristic in news and media reporting, and understanding what political biases people are exposed to when interacting with online news is of crucial import. However, quantifying political bias is problematic. To systematically study the political biases of online news, much of previous research has used human-labelled databases. Yet, these databases tend to be...
The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has better overall performance than single computatio...
Contagion dynamics in complex networks drive critical phenomena such as epidemic spread and information diffusion,but their analysis remains computa...
This study investigates the mechanisms of Surveillance Capitalism, focusing on personal data transfer during web navigation and searching. Analyzing...
Many surveillance cameras switch between daytime and nighttime modes based on illuminance levels. During the day, the camera records ordinary RGB im...
Accurately modeling and analyzing time series data is crucial for downstream applications across various fields, including healthcare, finance, astr...
Image retrieval methods rely on metric learning to train backbone feature extraction models that can extract discriminant queries and reference (gal...
The reproducibility of computational pipelines is an expectation in biomedical science, particularly in critical domains like human health. In this ...
We propose a pipeline for gaining insights into complex diseases by training LLMs on challenging social media text data classification tasks, obtain...
In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new...
With the emergence of large-scale vision-language models, realistic radiology reports may be generated using only medical images as input guided by ...
Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anom...
Age of Incorrect Information (AoII) is particularly relevant in systems where real time responses to anomalies are required, such as natural disaste...
Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs...
In this essay, we investigate some relations between Chemical Reaction Networks (CRN) and Mathematical Epidemiology (ME) and report on several pleas...
Artificial intelligence (AI) has become indispensable for managing and processing the vast amounts of data generated during the COVID-19 pandemic. O...
Infectious diseases occur when pathogens from other individuals or animals infect a person, resulting in harm to both individuals and society as a w...
We live in a world that is experiencing an unprecedented boom of AI applications that increasingly penetrate and enhance all sectors of private and ...
Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple...