Latest AI and machine learning research in infectious disease for healthcare professionals.
BACKGROUND: This study investigates malaria incidence trends in mainland China from 2005 to 2020, to elucidate its epidemiological characteristics and investigate potential associations with air pollution. Reasonable prediction is of great significance to control the epidemic of malaria. METHODS: First, time series analysis and machine learning methods were employed to predict malaria incidence. W...
Accurate forecasting of infectious disease cases and deaths is crucial for public health decision-making. Traditional statistical and machine learning approaches may be challenged by complex temporal patterns and heterogeneous surveillance data. We evaluated large language models (LLMs) for infectious disease forecasting. We collected monthly reported cases and deaths data from China National Noti...
OBJECTIVE: Early differentiation of pediatric acute respiratory infections in outpatient and emergency settings is often hindered by nonspecific clini...
Label-free surface-enhanced Raman spectroscopy (SERS) combined with machine learning (ML) provides a rapid, reagent-light approach to microbial detect...
Dental caries, periodontitis, oral mucosal inflammation, peri-implant infections, and oral tissue defects remain major clinical burdens. Conventional ...
Antimicrobial resistance (AMR) continues to outpace development of new therapeutics. Many interventions focus on treating infection after it occurs, b...
Ulcerative colitis (UC) is a chronic inflammatory bowel disease with limited non-invasive biomarkers and variable responses to probiotics. This study ...
Understanding how individual cells respond to genetic or environmental perturbations is crucial for deciphering disease mechanisms and advancing preci...
BACKGROUND: The global COVID-19 vaccine rollout faces challenges from persistent hesitancy, especially in rural and underserved regions. Alaska's uniq...
Antimicrobial resistance (AMR) is increasingly recognised as a One Health challenge in which environmental reservoirs play an important role in the pe...
Machine learning (ML) is necessary to efficiently identify potent drug combinations within a large candidate space to combat drug resistance. However,...
As IoT networks continue to evolve, concerns about their security risks are growing. Several security gaps still exist within IoT systems like Blackho...
Acinetobacter baumannii is a critical multidrug-resistant pathogen causing severe healthcare infections with high mortality, yet no licensed vaccine e...
Very early recurrence (within one year) after curative hepatectomy significantly impairs long-term survival in patients with hepatitis B virus (HBV)-r...
Multimodal large language models (LLMs) offer significant potential for image-based diagnostics, yet their reliability in routine clinical microbiolog...
Monkeypox (Mpox) is a viral disease that has garnered global attention due to its human-to-human transmissibility and cross-species transmission. Rece...
Biofilm-associated infections present a critical therapeutic challenge due to antibiotic resistance and impaired tissue healing. Here, we present a mi...
BACKGROUND: Convolutional neural networks (CNN) for skin cancer classification have shown results comparable to dermatologists but are vulnerable to m...
Viral proteases are critical targets in antiviral drug development due to their essential role in the viral lifecycle and high conservation across vir...
INTRODUCTION: Ischemic stroke remains a leading cause of death in the United States, with the COVID-19 pandemic exacerbating disparities. Prior studie...