Latest AI and machine learning research in infectious disease for healthcare professionals.
Background: We previously published a literature based pipeline for sepsis gene prioritization (PS3 and candidate genes) using an LLM enabled retrieval and judging framework. Here, we extend that work to ask whether these prioritized genes show independent clinical validity and whether the same strategy generalizes to a "drug/obesity/infection" setting. Methods: Using the original LLM guided workf...
Effective management of Bovine Respiratory Disease Complex (BRDC) requires timely, non-invasive diagnostic tools to protect calf health and welfare. Among early clinical signs, coughing stands out as both frequent and informative. To explore its potential for early BRDC detection, we deployed an artificial intelligence driven acoustic monitoring system that recorded over 2730 hours of audio during...
Oxygen is a primary driver of the distribution and activity of microbial life. Since oxygen levels are often difficult to measure in situ, one potenti...
Artificial intelligence systems for chest radiograph interpretation are increasingly deployed in clinical practice, yet current fairness frameworks em...
The escalating crisis of antimicrobial resistance poses a devastating and immediate threat to human life. Antimicrobial peptides (AMPs) are a promisin...
Structural elucidation using untargeted tandem mass spectrometry (MS/MS) has played a critical role in advancing scientific discovery. However, differ...
Dengue (DENV), an RNA virus, remains a significant global health threat, particularly in developing regions, with no widely effective antiviral therap...
Current remote sensing change detection (CD) methods mainly rely on specialized models, which limits the scalability toward modality-adaptive Earth ob...
Food wastage is one of the critical challenges in the agricultural supply chain, and accurate and effective spoilage detection can help to reduce it. ...
Sepsis remains one of the leading causes of mortality in intensive care units, where timely and accurate treatment decisions can significantly impact ...
Ecotoxicological tests with soil organisms, such as the collembolan Folsomia candida, are essential for assessing chemical risks in terrestrial ecosys...
Background: Deep learning algorithms for tuberculosis (TB) screening frequently achieve radiologist-level performance during internal evaluation, yet ...
The accurate identification of antiviral peptides (AVPs) is crucial for novel drug development. However, existing methods still have limitations in ca...
Selective knowledge erasure from LLMs is critical for GDPR compliance and model safety, yet current unlearning methods conflate behavioral suppression...
BackgroundSystemic infections are a leading cause of hospitalization and death among patients with cirrhosis. Timely and accurate infection identifica...
Numerous applications in research and medicine rely on reliable identification and quantification of virus-infected cells. Current methods either appl...
Accurately predicting how amino acid substitutions alter protein function is a central challenge in biology, with applications from interpreting disea...
Background: Pneumonia remains a leading cause of morbidity and mortality among children worldwide, emphasizing the need for accurate and efficient dia...
Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs)...
Despite over 13 billion SARS-CoV-2 vaccine doses administered globally, persistent post-vaccination symptoms, termed post-COVID-19 vaccine syndrome (P...