Latest AI and machine learning research in public health for healthcare professionals.
BACKGROUND: Intimate partner violence (IPV) and substance use disorders (SUDs) represent major public health challenges, yet identifying IPV cases in electronic health records (EHR) remains difficult due to inconsistent documentation practices and variable billing procedures. METHODS: We constructed three patient cohorts based on SUDs or overdoses involving stimulants, opioids, or both from the EH...
Intertwining supply chains integrates the corresponding networks across several intersection points, such as suppliers, manufacturers, and transporters, resulting in higher viability and efficiency. Nonetheless, no formulation has been proposed for intertwined logistics planning. In addition, interpretable machine learning models, such as multiple linear regression models, may not be an accurate m...
Cancer is associated with many pre-existing health conditions (PHCs), but accurately quantifying these links remains challenging. Although some studie...
OBJECTIVE: Public willingness to accept medical artificial intelligence (AI) tools affect the potential real-world impact of these evolving technologi...
Elucidating the gene regulatory networks (GRNs) that control human B cell differentiation is crucial for understanding immune responses to infection, ...
BACKGROUND: Inflammatory bowel disease (IBD) shows divergent epidemiological trends in China and the United States, necessitating country-specific for...
Cooling agents (chemicals added to impart a cooling sensation) in tobacco products are receiving increased attention due to their use as menthol subst...
AI solutions are frequently presented as promising solutions to a wide range of global challenges, including public health. However, the potential the...
Dengue remains a major mosquito-borne public-health threat, and climate change is expected to reshape the geographic suitability of its principal vect...
BACKGROUND: Prognostic information is essential for decision-making in breast cancer management. In recent years, trials and clinical practice have em...
OBJECTIVES: Artificial intelligence (AI)-driven chatbots have been rapidly adopted across research, education, business, marketing and medicine. Most ...
AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...
BACKGROUND: Bangladesh has a noticeable rise in vector-borne diseases (VBD) attributed to climate change. Accurately mapping, predicting, and identify...
Advances in multimodal longitudinal data and artificial intelligence (AI) create new opportunities for cancer etiology research. We envision an AI-pow...
The aims of the present study were to develop and validate a predictive model for lower limb Varicose Veins, and to visualize the results using a web ...
Personalized cancer vaccines have re-emerged as a promising strategy in precision immunotherapy, driven by advances in tumor sequencing, neoantigen id...
The rapid development of digital technologies is reshaping oral health research and care delivery. However, the translation of these innovations into ...
Artificial intelligence (AI) is now a key player in modern microbiology, as it enables high-resolution analyses of genomic, metagenomic, and clinical ...
Emerging infectious diseases are one of the most significant threats to global health, driven by many factors such as zoonotic spillovers, climate cha...
Artificial intelligence (AI) holds transformative potential for advancing oral health surveillance by streamlining data collection, integration, and d...