Latest AI and machine learning research in infectious disease for healthcare professionals.
The multi-round, solid-state fermentation process of sauce-flavor baijiu exhibits substantial fluctuations in baijiu yield. However, the microecological factors underlying yield variation and their regulatory strategies remain unclear. Here, we systematically examined microecological structure and physicochemical parameters from rounds 1 to 7 to explain yield variation. Rare microbial taxa, partic...
As a result of the increasing prevalence of Antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) in both community and hospital settings, their identification by conventional approaches has been posing a significant issue for decades. A new approach, integrating matrix-assisted laser desorption/ionization time of-flight mass spectrometry (MALDI-TOF-MS) with machine learning (M...
Multiple sequence alignments (MSAs) have been traditionally used for making inferences about site-specific diversity in proteins. Recent advancements ...
OBJECTIVE: This study aimed to develop and validate stratified machine learning models for early prediction of anti-tuberculosis drug-induced liver in...
A retrospective cohort study compared generative artificial intelligence (GenAI) versus infection control expert for catheter-associated urinary tract...
Vibrational spectroscopy has gained significant attention in medical diagnosis due to its high sensitivity and nondestructive nature. Raman spectrosco...
The tumor immune microenvironment and intratumoral microbiota play critical roles in cancer progression and immunotherapy response, yet their integrat...
Antimicrobial resistance (AMR) poses a critical and growing global health threat, directly causing millions of deaths, with China bearing a significan...
PURPOSE OF REVIEW: Post-traumatic care is evolving from a reactive, protocol-driven paradigm to a predictive, personalized approach. This review exami...
CLINICAL/METHODICAL ISSUE: Eosinophilic pneumonias are rare inflammatory lung diseases with heterogeneous clinical presentation and variable computer ...
Biological membranes are crucial for cellular integrity and function, but their selective permeability can be compromised by various peptides and prot...
The advancement of personalized medicine is increasingly reliant on wearable health monitoring technologies. While hydrogels offer great promise for s...
BACKGROUND AND PURPOSE: Accurate detection of pituitary microadenomas is critical for the diagnosis and treatment of Cushing's disease (CD). However, ...
BACKGROUND AND OBJECTIVE: Multidrug-resistant (MDR) bacterial infections are a leading cause of sepsis-related death. A rapid method to identify patie...
Dengue severity prediction models are usually developed using hospitalized patient data, but triage and hospital admission are mainly evaluated in out...
Despite advances in antiviral therapy, the rate of functional cure for chronic hepatitis B (CHB) remains unsatisfactory, and developing an applicable ...
OBJECTIVES: To apply unsupervised machine learning (ML) to predict outbreaks of respiratory tract infections (RTIs) in acute Irish hospitals (2016-202...
The large amount of data collected through automatic milking systems (AMS) may be used for early detection of intramammary infections and become instr...
In the last decades, critical advancements in research technology and knowledge on disease mechanisms steered therapeutic approaches for chronic infla...