Surveillance

Mapping Risk and Conservation Potential Across the Indo-Pacific with Reefshark Genomescapes

Overfishing has severely depleted marine populations worldwide, including within protected areas. Illegal and unreported fishing are major contributors to this decline. Large-bodied apex predators such as sharks are among the most affected, with overfishing causing dramatic species declines and ecosystem destabilization due to trophic downgrading. Key barriers to effective marine conservation and ...

Species-agnostic and Salmonella-specific Models for Antimicrobial Resistance Prediction Using FCGR and ResNet-18

Antimicrobial resistance (AMR) prediction from bacterial genomes remains a major challenge for clinical microbiology and surveillance. We developed deep learning models based on Frequency Chaos Game Representation (FCGR) and a ResNet-18 architecture to classify resistance phenotypes directly from whole-genome assemblies. Using homology-aware clustering to prevent genomic data leakage, we compared ...

Intelligent Tool Orchestration for Rapid Mechanistic Model Prototyping: MCP Servers as AI-Biology Interfaces

The construction of multicellular mechanistic models in systems biology typically requires months of literature research, programming expertise, and d...

Machine learning based lineage prediction from AMR phenotypes for Escherichia coli ST131 clade C surveillance across infection types

Rising antimicrobial resistance (AMR) in Escherichia coli bloodstream infections (BSIs) in high-income settings has typically been dominated by one cl...

Breaking the culture habit: metagenomic diagnosis of companion animal skin infections

Skin infections have been described as the primary cause for presentation in veterinary small animal practices and they frequently result in prescript...

Predicting Risk of Transfusion-Induced Red Blood Cell Alloimmunization Using Statistical and Machine Learning Approaches in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Database

Red blood cell (RBC) alloimmunization is a common complication from blood transfusion, often resulting in accelerated donor RBC destruction. Patients ...

A Machine Learning Approach Reveals CRISPR-Cas I-F as a Genomic Marker of Antibiotic Susceptibility in Uropathogenic E. coli

Antimicrobial resistance (AMR) in Escherichia coli is a critical global health challenge, particularly in urinary tract infections, where first-line t...

Structurally Informed Fitness Landscapes for Surveillance of Emerging PRRSV Variants

Antibodies play a central role in neutralizing pathogens through direct interference with viral entry and recruitment of effector immune cells. Howeve...

Contrastive learning of adverse events to provide effective and interpretable vector representations for machine-assisted pharmacovigilance

Post-marketing surveillance is crucial for drug safety, yet the tools of pharmacovigilance rely solely on text-based data that may limit the applicabi...

Machine learning–assisted selection of informative loci for strain-level phylogenetics of Neisseria gonorrhoeae

Epidemiological surveillance of Neisseria gonorrhoeae is hindered by the limitations of existing molecular typing methods, such as NG-MAST and MLST, w...

Systematic Review of Artificial Intelligence use in behavioral analysis of invertebrate and larval model organisms: Methods, Applications and Future Recommendations

Invertebrate and larval model organisms such as Drosophila melanogaster, Caenorhabditis elegans, Danio rerio larvae, and Galleria mellonella are incre...

Integrating theory and machine learning to reveal determinants of plasmid copy number

Plasmids are extrachromosomal mobile genetic elements whose copy numbers (PCNs) critically influence microbial evolution, antibiotic resistance and pa...

What kind of birds are more susceptible to avian malaria? A global analysis based on interpretable machine learning approach

Avian malaria (genus Plasmodium) is a mosquito-transmitted parasitic disease of birds. It has a wide distribution across the world, infecting more tha...

Explainable Machine Learning for Preoperative Relapse Prediction in Molecularly Stratified Endometrial Cancer: A Single-Center Finnish Cohort Study

Relapse risk in endometrial carcinoma (EC) is strongly influenced by molecular subtype, yet current WHO/ESGO classifications rely on postoperative dat...

Viral Sentry AI (VirSentAI) - Automated Zoonotic Surveillance & Drug Repurposing Agent

Zoonotic viruses capable of jumping from animal reservoirs into human populations represent a persistent and unpredictable menace to global health. To...

Electronic Health Record-Based Prediction Models to Inform Decisions about HIV Pre-exposure Prophylaxis: A Systematic Review

Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxi...

Large language models’ interpretation homogeneity and text Analysis: Evaluating the utility of the global flu view platform for Influenza surveillance

The advent of Large Language Models (LLMs) has transformed natural language processing and offers new possibilities for analyzing qualitative data in ...

SPIRIT-CONSORT-TM: a corpus for assessing transparency of clinical trial protocol and results publications

Randomized controlled trials (RCTs) can produce valid estimates of the benefits and harms of therapeutic interventions. However, incomplete reporting ...

EpiPathAI: Using Large Language Models to Explore Mechanisms of Life Course Exposure-Outcome Associations

Large language models (LLMs) enhanced with Graph Retrieval-Augmented Generation (GRAG) are promising for life-course epidemiology, which typically dep...

Using large language models to understand the public discourse towards vaccination in Brazil between January 2013 and December 2019

Vaccination against infectious diseases prevents diseases, saves lives, and reduces healthcare costs. However, trust, accessibility, and public percep...