Latest AI and machine learning research in public health for healthcare professionals.
BACKGROUND: Dengue transmission in Indonesia is shaped by interacting climatic, environmental, and socio-demographic factors, yet most forecasting systems remain static and vulnerable to data shifts. There is a critical need for adaptive, data-driven early-warning frameworks that integrate multiple predictor domains while preventing methodological biases such as information leakage. This study aim...
The recurrent outbreak of viral pathogens and the possibility of the new pandemics demand the transition to the predictive and integrative computational frameworks instead of reactive one. This review describes computational antiviralism as an integrated approach that uses artificial intelligence (AI), virtual screening, and molecular design tools to identify antiviral targets at the molecular lev...
BACKGROUND: Dengue risk is increasingly shaped by climate change and rapid urbanization, yet comprehensive, multidimensional risk assessments grounded...
PURPOSE: To evaluate the feasibility and diagnostic performance of ultra-low-dose CT (ULD-CT) for screening malignant metastasis using super-resolutio...
Heart failure (HF) remains a major global health challenge, characterized by high morbidity, mortality, and healthcare costs despite substantial advan...
Bovine tuberculosis (bTB) is a chronic zoonotic disease, caused by Mycobacterium bovis which despite years of eradication attempts, is still prevalent...
Avian pathology is the scientific study of diseases in birds, focusing on the structural, functional and molecular changes in tissues and organs cause...
Pandemic and epidemic intelligence integrates surveillance data with contextual knowledge to assess health risks and inform public health decisions. A...
BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) accounts for a substantial proportion of head and neck cancers, with a rising incidence larg...
BACKGROUND: Artificial intelligence and machine learning (AI/ML) may strengthen hospital infection prevention and control (IPC) through automated surv...
BACKGROUND: Rapid and accurate identification of intracellular pathogenic Brucella species and biovars is essential for effective public health survei...
Lung cancer persists as the predominant oncological cause of mortality globally, underscoring an imperative public health issue that demands effective...
Leprosy remains a neglected tropical disease with active transmission. Predictive models improve understanding of epidemiological trends and support c...
BACKGROUND: Central line-associated blood stream infection (CLABSI) surveillance is mandated and publicly reported in United States hospitals but requ...
Despite the reduced impact of COVID-19 due to widespread vaccination and improved treatments, a critical need remains for accessible, scalable, and ra...
OBJECTIVES: This study aimed to develop an effective model for predicting Hodgkin lymphoma (HL) prognosis as to assist clinicians in making optimal cl...
OBJECTIVES: Globally, dental reforms have gained momentum through enhanced policy dialogues, the rise of digital health, artificial intelligence and o...
The development of Artificial Intelligence (AI) is rapidly advancing, and AI tools are being integrated into many aspects of daily life, including med...
Respiratory syncytial virus (RSV) remains a major cause of severe acute respiratory infections across the life course, particularly in infants, older ...
Mosquito-borne diseases remain a major global health challenge, disproportionately impacting low- and middle-income countries. Despite traditional con...