Latest AI and machine learning research in infection control / modes of transmission for healthcare professionals.
Client attendance is vital for the success of HIV vertical transmission prevention programs, yet 23.4% of clients missed follow-up appointments after enrolling in a community health worker-led program (n=24,807, Aug-Dec 2022). Predicting which clients are most likely to miss appointments could enable targeted interventions to improve retention. While machine learning appears well-suited for this p...
Dengue fever remains a critical public health challenge in Thailand, with transmission dynamics driven by complex interactions between environmental and socioeconomic factors. Understanding these drivers is essential for developing robust prediction systems. We developed a machine learning framework to classify spatiotemporal dengue risk and identify key drivers of transmission across Thailand. We...
Tuberculosis remains a major health threat, infecting nearly a third of the world’s population. Of those infected, 5-10% progress from latent infectio...
Forecasting the effective reproductive number (Rt) and infection case counts is critical for guiding public health responses. We developed a machine l...
Sensitivity analysis is a key tool for identifying which model inputs most strongly influence model outputs thereby informing data collection prioriti...
Mucosal vaccines may reduce both infection and transmission by engaging local immunity, yet the immunological pathways they activate in humans remain ...
Dengue fever is a mosquito-borne viral disease with strong seasonality, periodicity, and spatial heterogeneity, posing a persistent global public heal...
Assessment of interstitial fibrosis is essential in the diagnosis and prognosis of kidney diseases. However, current histologic scoring methods using ...
Superspreading driven by individual variation in transmissibility shapes novel pathogen emergence and the effectiveness of control measures. Current a...
We study large language models (LLMs) for front-line, pre-diagnostic infectious-disease triage, a critically understudied stage in clinical interventi...
The estimates of national disease risk are considerably limited by the time of conducted surveys and the geographical inadequacies in surveillance, no...
Semantic communication (SemCom) is regarded as a promising and revolutionary technology in 6G, aiming to transcend the constraints of ``Shannon's tr...
Vector-borne diseases, including dengue, threaten the health and livelihoods of over 80% of the world's population, particularly in tropical and subtr...
Malaria Early Warning Systems (EWS) are predictive tools that often use climatic and other environmental variables to forecast malaria risk and trigge...
Personal protective equipment (PPE) is critical for ensuring the safety of construction workers. However, site surveillance images from construction s...
The likelihood of pedestrians encountering autonomous mobile robots (AMRs) in smart cities is steadily increasing. While previous studies have explore...
Dysregulated mitophagy is essential for mitochondrial quality control within human cancers. However, identifying hub genes regulating mitophagy and de...
Applying Large language models (LLMs) within specific domains requires substantial adaptation to account for the unique terminologies, nuances, and ...
Multi-band massive multiple-input multiple-output (MIMO) communication can promote the cooperation of licensed and unlicensed spectra, effectively e...
Tactile sensing is critical in advanced interactive systems by emulating the human sense of touch to detect stimuli. Vision-based tactile sensors ar...