Latest AI and machine learning research in public health & policy for healthcare professionals.
Cyber-attacks pose a security threat to military command and control networks, Intelligence, Surveillance, and Reconnaissance (ISR) systems, and civilian critical national infrastructure. The use of artificial intelligence and autonomous agents in these attacks increases the scale, range, and complexity of this threat and the subsequent disruption they cause. Autonomous Cyber Defence (ACD) agent...
Accurate barcode detection and decoding in Identity documents is crucial for applications like security, healthcare, and education, where reliable data extraction and verification are essential. However, building robust detection models is challenging due to the lack of diverse, realistic datasets an issue often tied to privacy concerns and the wide variety of document formats. Traditional tools...
Video Anomaly Detection (VAD) aims to automatically analyze spatiotemporal patterns in surveillance videos collected from open spaces to detect anom...
Artificial Intelligence (AI) and infectious diseases prediction have recently experienced a common development and advancement. Machine learning (ML...
Periodontal disease is a common and frequently-occurring disease in China. Early detection, diagnosis, and treatment of periodontal disease are of gre...
Traditional Chinese medicine has accumulated a wealth of experiences in individualized cancer prevention and serves as a complement to Western medicin...
Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancement...
Artificial intelligence (AI) and machine learning (ML) are important tools across many fields of health and medical research. Pharmacoepidemiologists ...
The problem of attacks on new generation network infrastructures is becoming increasingly relevant, given the widening of the attack surface of thes...
Major software failures are reported to be due to misconfiguration. As manual configuration is too error-prone to be deemed a reliable strategy for ...
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...
This study develops a cloud-based deep learning system for early prediction of diabetes, leveraging the distributed computing capabilities of the AW...
In a world burdened by air pollution, the integration of state-of-the-art sensor calibration techniques utilizing Quantum Computing (QC) and Machine...
Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This study aimed to compare the performance of multiple...
Mathematical modelling has served a central role in studying how infectious disease transmission manifests at the population level. These models hav...
Population based health data collection and analysis are important in epidemiological research. In recent years, with the rapid development of big dat...
Reconstructing transmission networks is essential for identifying key factors like superspreaders and high-risk locations, which are critical for de...
Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed based on single-modal biochemical tests, and imaging...
Due to the importance of COVID-19 control, innovative methods for predicting cases using social network data are increasingly under attention. This st...