Infectious Disease

CARD:Epi - Contextualizing Antimicrobial Resistance Determinants Using Deep Learning Language Models

Bacterial outbreak publications outline the key factors involved in the uncontrolled spread of infection. Such factors include the environment, pathogens, hosts, and antimicrobial resistance genes (ARGs). Individually, each paper published in this area gives a glimpse into the devastating impact drug resistant infections have on healthcare, agriculture, and livestock. When examined together, these...

Learning from human and chemical languages to predict biological function

Understanding how molecular structure encodes biological function remains a grand challenge in drug discovery. Here, we present PubCheF-1, a deep learning model that predicts literature-derived biological function directly from chemical structure. PubCheF-1 was trained on a dataset linking molecules to labels derived from the scientific articles in which they appear, a strategy that connects dispa...

The Role of Natural Language Understanding in Multimodal Video-Based Dengue Diagnosis

Detecting infection-related behavioral changes in mosquitoes from video data is challenging because mosquitoes are small, move rapidly and irregularly...

A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench

General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but s...

Unmasking Toxic Mimicry in Medical Offline Reinforcement Learning for ICU Sepsis Management via Counterfactual Clinical Audits

Offline reinforcement learning (RL) offers considerable promise for optimizing ICU treatment decisions, yet standard evaluation metrics Mean Squared E...

On-Device Multi-Species Malaria Detection with Uncertainty-Calibrated Slide-Level Aggregation

Malaria remains a leading cause of mortality in resource-limited settings, where expert microscopists are scarce. Automated diagnosis based on microsc...

A membrane-impermeant nucleic acid dye converts bacteriophage plaque assays into a machine-readable format for automated counting

Plaque assays remain the gold standard for bacteriophage quantification, but routine plaque counting is labor-intensive, time-consuming, and poorly su...

Mapping the Pandemics Echo: Dynamic Narrative Detection and Spatio-Temporal Sentiment Modeling of COVID-19 Discourse on Twitter

The COVID-19 pandemic triggered an unprecedented volume of real-time discourse on social media platforms, with Twitter serving as a global forum for p...

Regional and Temporal Patterns of COVID-19 Vaccine Misinformation in Sub-Saharan Africa

BackgroundDespite a global rollout of COVID-19 vaccines, Sub-Saharan Africa lagged behind other regions in vaccination coverage, driven primarily by i...

RiboRep: Replicate-Aware Cross-Modal Transformers for Codon-Resolved Ribosome Density Prediction

Ribosome profiling enables genome-wide measurement of translation at nucleotide resolution and provides a dynamic view of cellular protein synthesis u...

Structure-aware deep learning predicts influenza antigenicity and guides vaccine strain recommendation

The continuous accumulation of genetic mutations in influenza A viruses (IAVs) drives antigenic drift, necessitating precise antigenic prediction for ...

MIRA: an open source and user-friendly software to automate counting and sizing of fungal spores

Background The quantification of fungal spores constitutes a fundamental metric in phytopathology, serving as the primary variable for inoculum standa...

Deep learning-guided identification of bacteriophage receptor-binding protein candidates for foodborne pathogen detection

Foodborne pathogens including Salmonella spp., Escherichia coli and Listeria monocytogenes cause an estimated 600 million illnesses annually. Yet conv...

Multimodal artificial intelligence using entire electronic health record and complete pathogen genome data for patient outcome prediction from life-threatening infection: the SuperbugAI Platform

Artificial intelligence (AI) has the potential to transform healthcare, with advanced multimodal approaches showing great promise in leveraging divers...

AI-guided discovery of antimicrobial peptides for urinary tract infections leveraging a new catalogue of the human urinary microbiome

Urinary tract infections (UTIs) are common infections that pose a critical burden on healthcare and society. Despite growing recognition that the huma...

Predictive models for hospitalization and mortality in dengue using SINAN data: study protocol for development, temporal validation, and performance evaluation

Background: Dengue continues to place a heavy clinical and organizational burden on health care systems, particularly during epidemics, when the high ...

Bayesian Spatiotemporal Small-Area Estimation of HIV Testing Uptake in Ghana, 2008-2022: Integrating Machine-Learning-Derived Geospatial Covariates with District-Level BYM2-RW1 Modelling of the Ghana Demographic and Health Surveys

Background: HIV testing is the entry point into the diagnosis, treatment and viral suppression cascade, yet in many low and middle income countries th...

Automated classification method of COVID-19 cases from chest CT volumes using 2D and 3D hybrid CNN for anisotropic volumes

This paper proposes an automated classification method of chest CT volumes based on likelihood of COVID-19 cases. Novel coronavirus disease 2019 (COVI...

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID...

Interpretable machine learning prediction of in-hospital mortality in ICU patients with cancer and sepsis using first-day data: Development using MIMIC-IV and external validation in eICU-CRD

Background: Critically ill patients with cancer and sepsis have high in-hospital mortality, but externally validated prediction models are limited. Ob...