This study reveals shadow antibiograms—pathogen- and setting-specific antibiotic testing patterns that shape which antimicrobial resistance data enter survei...
UbiQVision is an explainable AI framework for reliable deep vision ensembles in medical imaging. It combines Dirichlet posterior sampling, SHAP attribution m...
A hybrid interactive approach for summary polar diagrams, such as Taylor and mutual information diagrams, that combines aggregation, filtering, Cartesian lin...
Radial visualization is widely used for analyzing complex multivariate data, but its interactive capabilities remain inconsistent across modern visualization...
PepTriX is an open-source framework for peptide classification that combines 1D sequence embeddings with 3D structural features using graph attention network...
The Open Syndrome Definition is the first open, machine-readable standard for public health case definitions, improving interoperability, data sharing, and e...
This study examines ensemble machine learning for genomic island detection, a key driver of antimicrobial resistance spread. Combining diverse data represent...
Genomic AI models like Nucleotide Transformer and Evo are advancing DNA and protein design, enabling breakthroughs such as AI-created bacteriophages. However...
This review analyzes AI methods for peptide detectability prediction in proteomics, highlighting gaps in reproducibility and transparency. It proposes guidel...
This scoping review examines the role of artificial intelligence in advancing syndromic surveillance, analyzing 15 key studies to provide eight strategic rec...
UbiQTree quantifies uncertainty in SHAP explanations for tree ensemble models, decomposing it into aleatoric (irreducible) and epistemic (reducible) componen...
RCKmer (k=7) + SVM representation achieves state-of-the-art HGT detection (F1=0.959, MCC=0.908) across 44 genomic encodings and 4 datasets, outperforming tra...
Ten persona-adaptable strategies enable large language models to self-explain their functionality to everyday users, tailoring complexity/style to user arche...
Protocol for implementing the nested model to develop/validate AI systems compliant with regulations, spanning domain, data, model, and prediction layers wit...
Review reveals surging AI adoption in Horizontal Gene Transfer (HGT) detection—a key driver of prokaryotic evolution and antimicrobial resistance (AMR)—with ...
Kernel ridge regression enables safe tracking control for high-order dynamical systems with unknown dynamics and partial state observations. Our observer-int...
iCAN delivers interpretable carbon-neighborhood encodings for organic molecules, outperforming prior methods in peptide/protein classification across large b...
polar-diagrams is an interactive library implementing Mutual Information and Taylor Diagrams to visualize multi-model performance across biology, medicine, c...
The rapid growth of high-throughput technologies has led to increasingly complex, high-dimensional datasets that challenge traditional storage and analysis m...
We propose cmangoes, a parametric, carbon-chain-based encoding method for organic molecules that generates binary/numerical arrays (exportable as images) fro...
MOVIS is a modular, web-based tool for exploring time-series multi-omics data, designed to make complex temporal, multi-modal datasets accessible to research...
Data creation is rapidly outpacing traditional storage, driving the need for new media such as DNA storage. This work surveys user requirements across key st...
Protein function often depends on post-translational modifications such as N-linked glycosylation, a key process linked to many diseases. Experimental detect...
