Latest AI and machine learning research in infection control for healthcare professionals.
Antibiotic resistance is a critical public health threat, particularly in hospital settings where vulnerable populations face heightened risks of infection and adverse outcomes. Forecasting resistance trends at the facility level is essential for guiding local antibiotic stewardship, informing infection control strategies, and improving patient safety. In this study, we conducted a comparative eva...
Continuous quality improvement is essential in surgery, with clinical registries and quality improvement programs (QIPs) playing a key role. Postoperative complications (PCs) require substantial resources to manage, yet traditional QIPs are expensive and often lays a significant labor burden on clinicians in data collection. Artificial intelligence (AI), particularly natural language processing (N...
Tuberculosis remains a major global health concern, particularly in high-burden countries where early detection is essential but often limited by insu...
Emergency department (ED) crowding strains patient care and drives up costs. Early decisions on the need for patient hospital admissions can allow for...
Respiratory infections are a leading cause of pediatric emergency visits globally, requiring timely and accurate assessment. This study evaluated the ...
Rapid innovation and new regulations increase the need for post-marketing surveillance of implantable devices. However, complex multi-level confoundin...
During the COVID-19 pandemic, the field of infectious disease modeling advanced rapidly, with forecasting tools developed to track trends in transmiss...
Efficient patient monitoring on the medical-surgical wards is crucial to prevent significant in-hospital adverse events. Standard episodic inpatient a...
Combined Pulmonary Fibrosis and Emphysema (CPFE), formally recognized as a distinct pulmonary syndrome in 2022, is characterized by unique clinical fe...
Accurately predicting clinical trajectories in critically ill patients remains challenging due to physiological instability and multisystem organ dysf...
The open-source release of DeepSeek-R1, a high-performing large language model (LLM), enables local deployment in Chinese hospitals. However, empirica...
To develop and evaluate an open-source machine learning (ML) models for predicting hospital short stays (length of stay [LOS] under 48 and 72 hours) e...
Advancements in artificial intelligence (AI) are revolutionising the healthcare sector, but challenges exist in AI adoption and its long-term use. Thi...
Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in healthcare settings, its precise kinetics and real-w...
Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness. Since delay in initiation of ECT can have detrim...
In clinical settings, patients often express dissatisfaction through narrative speech or written text. However, most complaints management systems sti...
The early recognition of clinical deterioration in hospital inpatients continues to be a major challenge in healthcare. In this work, we proposed an i...
Carbapenem resistance in Pseudomonas aeruginosa is increasing in intensive care units (ICUs). To enhance antimicrobial stewardship and infection contr...
This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy, i.e. a clinical presentation consistent with bac...
Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection is essential for improving survival through timel...