Latest AI and machine learning research in infectious disease for healthcare professionals.
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...
Microorganisms represent the most taxonomically and functionally diverse components of freshwater environments. Whilst distinct microbial communities exist across freshwater habitats, such as the water column and sediments, epilithic and epiphytic biofilm communities are critical in performing key roles in biogeochemical cycling and freshwater food webs. Despite their biogeochemical and ecological...
BACKGROUND: Quantitative polymerase chain reaction (qPCR) is a fundamental tool for disease detection; however, the relatively large number of amplifi...
The rapid escalation of antimicrobial resistance (AMR) represents a major global health challenge, undermining the clinical efficacy of conventional a...
IMPORTANCE: Decision aid tools are well-utilized resources in shared decision making for the treatment of pelvic floor disorders. With the improvement...
INTRODUCTION: Teicoplanin is commonly used to treat Gram-positive bacterial infections in the intensive care unit (ICU). However, evidence to support ...
Transposable elements (TEs) are parasitic genomic elements that are ubiquitous across the tree of life and play a crucial role in genome evolution. Ad...
Cancer is associated with many pre-existing health conditions (PHCs), but accurately quantifying these links remains challenging. Although some studie...
BACKGROUND: Reliable predictive modeling in high-dimensional biomedical data requires a balance between accuracy, interpretability, and computational ...
Bacteremia is a major contributor to global morbidity and mortality, particularly in low- and middle-income countries where diagnostic delays and empi...
OBJECTIVE: Public willingness to accept medical artificial intelligence (AI) tools affect the potential real-world impact of these evolving technologi...
BACKGROUND: Prolonged muscle loss and persistent pulmonary radiological manifestations have been observed among previously hospitalized COVID-19 patie...
OBJECTIVES: To develop and validate an explainable artificial intelligence (XAI)-based machine learning (ML) model for predicting infections requiring...
The high specificity of phages toward their hosts holds great promise for phage therapy while posing a challenge to computational prediction approache...
Early HIV detection using noninvasive samples remains challenging because oral fluid contains extremely low antibody levels and enzymatic inhibitors t...
BACKGROUND: Large language models (LLMs) could accelerate clinical literature searches, but their reliability is compromised by "hallucinations" gener...
BACKGROUND: Chest X-ray (CXR) can assess pulmonary tuberculosis (TB) severity and may guide duration of treatment. However, the optimal radiological m...
Elucidating the gene regulatory networks (GRNs) that control human B cell differentiation is crucial for understanding immune responses to infection, ...
Automated function prediction (AFP) is the process of predicting the function of genes or proteins with machine learning models trained on high-throug...
Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1), encoded by the hypervariable var gene family, is central to malaria pathogenesis, influ...