Latest AI and machine learning research in public health & policy for healthcare professionals.
Current circulating biomarkers for idiopathic pulmonary arterial hypertension (IPAH) lack specificity for preclinical detection and fail to capture the biological heterogeneity driving disease progression. Furthermore, molecular mechanisms underlying the “sex paradox” of IPAH, where females exhibit higher susceptibility but lower mortality, remain poorly understood, hindering the development of pr...
The course of psychotic disorders typically involves relapses. Early warning signs vary between individuals and are difficult to detect in clinical practice, especially in outpatient settings. Speech provides a quantitative clinical marker for detecting such early warning signs. The EU Horizon project TRUSTING (A TRUSTworthy speech-based AI monitoring system for the prediction of relapse in indivi...
Pathology reports contain the most detailed descriptions of cancer diagnoses, yet their unstructured format has long limited large-scale reuse for can...
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...
Accurate ship valuations are very important in ship sales and purchase (S&P) transactions and for marine insurance purposes. It is equally important t...
Intimate Partner Violence (IPV) is a major public health problem to be addressed with innovative and interconnecting strategies for ensuring the psych...
Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2-8% of all pregnancies ...
Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic disparities, poor sanitation, and environmental fa...
Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet existing methods often struggle with accuracy and robu...
BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwide. Coronaviruses cause diseases such as severe ac...
Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was diffic...
We propose a new theory of information-based voluntary social distancing in which people's responses to disease prevalence depend on the credibility o...
The rapid development and integration of interconnected healthcare devices and communication networks within the Internet of Medical Things (IoMT) hav...
The chemotherapy benefit for high-grade chondrosarcoma remains controversial. Ensemble learning has better overall performance than single computatio...
In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pandemics, there is a need for tools that can address...
Wireless Sensor Networks (WSNs) continue to experience rapid developments and integration into modern-day applications. Overall, WSNs collect and pr...
Contagion dynamics in complex networks drive critical phenomena such as epidemic spread and information diffusion,but their analysis remains computa...
The development of deep learning has facilitated the application of person re-identification (ReID) technology in intelligent security. Visible-infr...
The collection of updated data on social contact patterns following the COVID-19 pandemic disruptions is crucial for future epidemiological assessme...