Latest AI and machine learning research in public health for healthcare professionals.
Sensitivity analysis is a key tool for identifying which model inputs most strongly influence model outputs thereby informing data collection priorities. In agent-based models, these inputs include demographic parameters used to construct synthetic populations. Such parameters — age distributions, household size distributions, and contact matrices — are critical in shaping transmission dynamics. H...
To evaluate whether machine learning (ML) applied to comprehensive claims data without diagnostic codes can distinguish a high proportion of antibiotic treatment episodes as urinary tract infection (UTI) or non-UTI cases. Such approaches may be valuable for antimicrobial stewardship when diagnosis-linked datasets are unavailable. Outpatient antibiotic prescription claims from three major Swiss ins...
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...
Clinicopathologic calculators for bladder cancer moderately predict survival and fail to depict the underlying molecular phenotype. We applied urinary...
Respiratory disease outbreaks burden U.S. healthcare systems with over one million hospitalizations annually, yet current surveillance systems lag 1-2...
Falls among elderly residents in assisted living facilities (ALFs) are prevalent, costly, and frequently under-documented. AUGi, a wall-mounted device...
Skin neglected tropical diseases (NTDs) such as cutaneous leishmaniasis, lymphatic filariasis, mycetoma, and podoconiosis affect millions in endemic r...
Large language models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks, including text classification, in...
Accurate, affordable tuberculosis (TB) diagnostics that do not require sputum samples are urgently needed for TB control and elimination. Prior serolo...
Simulation models inform health policy decisions by integrating data from multiple sources and forecasting outcomes when there is a lack of comprehens...
The 2022 global outbreak of clade IIb mpox represented a turning point in public health’s handling of poxviruses. The primary vaccine available for pr...
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...
The Charlson Comorbidity Index (CCI) is widely used in epidemiologic studies. However, many versions of the CCI have been developed since the original...
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...
Sex differences in the humoral immune responses to the seasonal quadrivalent influenza vaccine (QIV) in young adults (YA; 18-49yo) or high dose QIV in...
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...